2019 Online Dating Study PDF

FROM FIRST EMAIL TO FIRST DATE The paper titled “From First Email to First Date: Strategies for Initiating Relationships in Online Dating,” authored by Liesel L. Sharabi and Tiffany A. Dykstra-DeVette, published in the Journal of Social and Personal Relationships in 2019, explores the myriad strate...

FROM FIRST EMAIL TO FIRST DATE The paper titled “From First Email to First Date: Strategies for Initiating Relationships in Online Dating,” authored by Liesel L. Sharabi and Tiffany A. Dykstra-DeVette, published in the Journal of Social and Personal Relationships in 2019, explores the myriad strategies employed by individuals seeking to initiate relationships on online dating platforms. The study is grounded in three foundational communication theories: the Hyperpersonal Model, Uncertainty Reduction Theory, and Social Penetration Theory. The authors analyze data from 105 online daters, comprising predominantly women, to discern patterns in relationship initiation strategies, gender differences in these strategies, and the correlation between these strategies and the success of first dates. The Hyperpersonal Model posits that computer-mediated communication can lead to enhanced intimacy and idealized impressions through selective self-presentation and overattribution of positive qualities. Uncertainty Reduction Theory suggests that individuals engage in specific behaviors to mitigate uncertainty regarding potential partners, while Social Penetration Theory illustrates the progression of relationship development through incremental self-disclosure. The authors formulated three research questions: (RQ1) What strategies do people use to initiate relationships on online dating sites? (RQ2) What gender differences exist in relationship initiation strategies in online dating? (RQ3) How are initiation strategies related to the success of the first offline date? The methodology involved qualitative content analysis of 207 pages of email conversations collected from online dating platforms such as Tinder and OkCupid. The analysis yielded seven main categories and 18 subcategories of relationship initiation strategies. Furthermore, statistical tests were employed to explore gender differences and the relationship between initiation strategies and first-date outcomes. Key findings revealed that certain strategies, such as discussing partner preferences, significantly increased the likelihood of securing a second date, while others, like mentioning relationship alternatives, negatively impacted this likelihood. Gender differences emerged, with men more likely to initiate contact and utilize certain types of pickup lines, while women tended to focus on highlighting dissimilarities. The study contributes to theoretical understanding by affirming the relevance of the Hyperpersonal Model and illustrating how self-presentation and disclosure in online contexts influence offline relationship dynamics. Highlights Diverse Initiation Strategies: The study identified seven main categories of strategies used by individuals initiating relationships online. Gender Norms Persist: Traditional gender roles remain evident in online dating, with men primarily taking the initiative in first contact. Impact of Preferences: Discussing partner preferences correlates with a higher likelihood of securing a second date. Negative Impact of Alternatives: Mentioning relationship alternatives can decrease the chances of a second date. Incremental Disclosure: The importance of self-disclosure in fostering intimacy and managing uncertainty in online interactions is highlighted. Relevance of Communication Theories: The study reinforces existing theories on communication, showcasing how they apply in the online dating context.  Statistical Insights: Gender differences in strategy use were statistically significant, emphasizing the need to understand these dynamics for effective online dating. Key Insights Diverse Initiation Strategies: The research identified seven main categories of initiation strategies, with 18 distinct subcategories. This diversity underscores the complexity of relationship initiation in online contexts. Strategies included various approaches to first contact, mate selection, authenticity construction, and transitioning offline. Understanding these strategies can help individuals navigate online dating more effectively, tailoring their approaches based on context and personal goals. Gender Norms Persist: The study found that men were significantly more likely to initiate contact compared to women, reflecting traditional gender norms. This pattern suggests that, despite the anonymity of online platforms, societal expectations around dating dynamics continue to influence behavior. This insight is crucial for users to recognize potential biases and strategize accordingly when engaging in online dating. Impact of Preferences: Participants who discussed their partner preferences had a notably higher likelihood of securing a second date. This finding emphasizes the importance of communicating personal expectations and desires clearly during the initial interactions. It suggests that individuals should adopt a proactive approach in expressing their relationship goals to enhance compatibility and connection with potential partners. Negative Impact of Alternatives: Mentioning relationship alternatives negatively correlated with the likelihood of a second date. This finding indicates that emphasizing alternatives may signal indecision or lack of commitment, which can deter potential partners. Individuals should be mindful of how they frame their conversations and avoid language that implies they are exploring multiple options simultaneously. Incremental Disclosure: The study aligns with Social Penetration Theory, highlighting that successful online daters engage in incremental self-disclosure. This gradual sharing of personal information fosters deeper connections and reduces uncertainty about compatibility. Individuals should consider pacing their disclosures to build trust and intimacy over time. Relevance of Communication Theories: The research extends the Hyperpersonal Model by demonstrating how online dating fosters idealized perceptions and affects real-life relationship outcomes. This theoretical validation underscores the need for further exploration of how online communication shapes interpersonal dynamics in various contexts, particularly as dating technologies evolve. Statistical Insights: The use of statistical analysis revealed significant gender differences in strategy use, with men favoring certain types of initial messages and women more often emphasizing differences. These insights suggest that awareness of gendered communication patterns can enhance users’ effectiveness in online dating, allowing them to adjust their strategies to resonate more effectively with their intended audience. In conclusion, the paper by Sharabi and Dykstra-DeVette provides valuable insights into the strategies employed in online dating, revealing the complexities of initiating relationships in a digital landscape. By understanding the dynamics of communication and the influence of gender norms, online daters can enhance their experiences and outcomes in the quest for meaningful connections. ANTECEDENTS AND OUTCOMES OF DIGITAL INFLUENER ENDORSEMENT The paper titled “Antecedents and Outcomes of Digital Influencer Endorsement: An Exploratory Study,” authored by Pedro Torres, Mário Augusto, and Marta Matos, was published in Psychology & Marketing in 2019. The study primarily examines how the attractiveness of digital influencers—defined through their likeability and familiarity—and the brand congruence, or the alignment between the influencer’s image and the brand’s identity, impact consumer attitudes towards brands and their intentions to purchase. This research addresses a significant gap in the marketing literature by extending the established insights from celebrity endorsements to the realm of digital influencer marketing, a rapidly growing area in the digital landscape. The study identifies digital influencers as socially influential individuals with substantial followings on platforms like Instagram and YouTube. Unlike traditional celebrities, digital influencers are often perceived as more relatable and authentic, which enhances their effectiveness in shaping consumer behavior. The authors employ the Meaning Transfer Model, originally proposed by McCracken in 1989, to explain how these influencers can transfer symbolic meanings to brands, thereby influencing consumer attitudes and behaviors. The research is structured around several hypotheses, primarily focusing on the relationship between influencer attractiveness, brand congruence, and outcomes such as brand attitudes and purchase intentions. The study’s methodology involved a survey of 307 Portuguese social media users, predominantly young females who follow various digital influencers. Data collection utilized a structured online questionnaire, and the results were analyzed through Structural Equation Modeling (SEM). Findings from the study support the proposed hypotheses, indicating that influencer attractiveness positively influences brand congruence, attitudes toward the endorsement, attitudes toward the brand, and ultimately, purchase intentions. Notably, it was found that brand congruence has a stronger impact than attractiveness alone on consumer attitudes and purchasing behavior. Additionally, the study confirms that both endorsement attitude and brand attitude serve as mediators in the relationship between influencer characteristics and purchase intentions. The conclusions drawn from the research underscore the importance of aligning influencer and brand identities. Brands must prioritize selecting influencers who resonate with their values to maximize the effectiveness of endorsement strategies. The research further highlights the dual mediation of affective (emotional) and cognitive (rational) evaluations in shaping consumer behavior. The study’s contributions extend existing theories of celebrity endorsement to digital influencers and emphasize the significance of understanding the dynamics of influencer marketing. However, the authors acknowledge certain limitations, including a sample restricted to Portuguese consumers and two distinct product categories. They suggest that future research should consider a broader scope, exploring diverse consumer segments and various product categories. Moreover, investigating the impact of endorsement execution styles on effectiveness could provide valuable insights into optimizing influencer marketing strategies. Highlights Influencer Attractiveness Matters: Likeability and familiarity of digital influencers significantly impact consumer attitudes and purchase intentions. Brand Congruence is Key: The alignment between the influencer and brand identity plays a crucial role in enhancing the effectiveness of endorsements.  Dual Mediation Confirmed: Both attitudes toward the endorsement and the brand mediate the relationship between influencer characteristics and purchase intentions. Strategic Selection of Influencers: Brands should prioritize selecting influencers who align closely with their values for successful marketing campaigns. Emotional and Rational Evaluations: The study highlights the interplay between affective and cognitive evaluations in shaping consumer behavior. Research Limitations: The study’s sample size and scope were limited, suggesting the need for further research in diverse contexts. Future Research Directions: Recommendations include exploring a wider array of product categories and examining endorsement execution styles. Key Insights Influencer Authenticity: Influencers are perceived as more relatable than traditional celebrities, which enhances their effectiveness in marketing. This authenticity fosters a sense of trust among consumers, making them more likely to engage with brands endorsed by these influencers. Impact of Brand Congruence: The study illustrates that a strong fit between the influencer and the brand leads to more favorable consumer attitudes and increased purchase intentions. This finding emphasizes the need for brands to assess potential influencers not just on popularity, but on their alignment with brand values and image. Balancing Affective and Cognitive Responses: The results suggest that both emotional and logical evaluations influence consumer behavior. Consumers may feel an emotional connection to an influencer while also evaluating the brand based on rational criteria, showcasing the complexity of consumer decision-making. Meaning Transfer in Influencer Marketing: The research reinforces the Meaning Transfer Model as a critical framework in understanding how influencers can effectively convey brand messages and values to their audience, thereby influencing consumer perceptions and behaviors. Generalizability of Findings: The multigroup analysis conducted in the study indicates that the results are consistent across different categories, such as Entertainment & Video Games and Fashion & Beauty. This suggests that the findings may be applicable to a broader audience beyond the initial sample. Managerial Implications: The findings offer practical insights for marketers, highlighting the importance of selecting influencers who resonate with the target audience’s values and preferences. This strategic alignment can enhance the effectiveness of marketing campaigns and drive consumer engagement. Need for Diverse Research: The paper advocates for future studies to expand the scope and diversity of samples to better understand how various demographic factors influence the effectiveness of influencer endorsements across different product categories. In summary, this exploratory study provides valuable insights into the dynamics of digital influencer marketing, establishing a foundation for further research in this evolving field. The implications for both theory and practice underscore the importance of influencer characteristics, brand congruence, and the dual mediation of consumer attitudes in driving purchase intentions. DIGITAL EMOTION CONTAGION The paper explores the concept of digital emotion contagion, which refers to the phenomenon where individuals’ emotional expressions become more aligned with those of others due to exposure through digital media. The review highlights that this contagion is uniquely mediated by digital platforms that often aim to enhance user emotions for engagement. The authors define emotion contagion, examine measurement challenges, and propose the need for deeper understanding of the conditions under which contagion occurs, discussing factors such as the nature of expressed emotions, network connections, user characteristics, and platform dynamics. The review also addresses the historical context, key mechanisms, and implications for social movements, concluding with future research directions in this evolving field. Highlights Definition of Digital Emotion Contagion: A phenomenon where emotional expressions become similar due to exposure through digital media platforms. Mediated Emotion Contagion: Digital media companies play a crucial role in shaping emotional expressions, often aiming to enhance user engagement. Measurement Challenges: Identifying when contagion occurs is difficult due to the multitude of influencing factors and the need for robust measurement techniques. Impact on Social Movements: Digital media has transformed social movements by facilitating the rapid spread of emotions like anger, which can lead to collective action. Mechanisms of Contagion: Emotion contagion can occur through mimicry, category activation, and social appraisal, affecting both individual and collective emotional dynamics. User Characteristics: Individual differences such as personality traits and online behavior influence susceptibility to digital emotion contagion. Platform Dynamics: Different digital platforms have varying emotional baselines that can impact the nature and strength of emotional contagion among users. Key Insights Digital Emotion Contagion as a Mediated Process: The authors argue that unlike traditional emotion contagion, which happens face-to-face, digital emotion contagion is mediated by platforms that often prioritize emotional engagement. This means that the emotional content users are exposed to is curated to maximize interaction, potentially amplifying the contagion effect. Challenges in Measurement: Accurately measuring emotion contagion in digital contexts involves overcoming significant hurdles. Researchers must track emotional states before and after exposure to others’ emotions, which is complicated by the vast array of variables that can influence emotional changes. The paper discusses various methodologies that have been employed to estimate emotional expressions and the content users encounter. Ubiquity and Implications for Social Movements: The review highlights the critical role of digital emotion contagion in contemporary social movements. The case of Khaled Mohamed’s death illustrates how emotions expressed online can catalyze widespread collective action. The authors stress that while digital media has empowered social movements, the transition from online engagement to real-world activism can be inconsistent.  The Role of Expressed Emotions: The nature and intensity of the emotions expressed significantly influence contagion. While there is some debate about whether positive or negative emotions are more contagious, the prevailing view suggests that both can have substantial effects depending on the context. Future research should clarify which types of emotions are most influential in specific situations. Network Connection Dynamics: The strength of the connection between the expresser and the perceiver plays a crucial role in the contagion process. Research indicates that stronger ties may facilitate contagion differently based on the emotional content being shared, with anger spreading more effectively through weaker ties, while joy may be more impactful among closer connections. Individual Differences Matter: User characteristics such as personality traits (e.g., extraversion, neuroticism) and online behavior patterns (e.g., activity level) significantly affect susceptibility to digital emotion contagion. Understanding these differences can help predict when and how contagion effects manifest among users. Future Research Directions: The authors call for a shift in research focus from simply proving that contagion occurs to understanding under what conditions it is strongest or weakest. Investigating the interplay between expressed emotions, user characteristics, and platform dynamics will be crucial for advancing the field of digital emotion contagion. Conclusion The exploration of digital emotion contagion reveals the complexity of emotional dynamics in the age of digital media. As users increasingly engage with emotional content online, understanding the mechanisms, measurement challenges, and implications for behavior becomes essential. The review emphasizes the need for further research to uncover the nuanced factors that drive this phenomenon, with particular attention to how digital platforms mediate emotional experiences and expressions. As digital media continues to evolve, so too will our understanding of how emotions spread and influence collective behavior in both online and offline contexts. NOTES Summary The text outlines a comprehensive framework for understanding the psychological implications of digital media use, focusing on the interplay between cognition, social behavior, and technology. It delves into various psychological theories that explain how individuals interact with digital platforms, emphasizing the significance of empathy in both pro-social and anti-social behaviors online. The document also addresses the evolution of communication in the digital age, detailing how technology has reshaped cognitive functions such as attention, memory, and emotional responses. Moreover, it highlights the consequences of these changes for individual mental health, social dynamics, and community structures, offering insights into the dual nature of digital media as both a facilitator of connection and a source of conflict. Highlights Course Structure: The course will include statistical assessments, participation, and assignments that contribute to a total of 50 hours of learning, with a focus on both theoretical and practical aspects of psychology in digital media. Psychology Definition: Psychology is defined as the scientific study of behavior and mental processes, distinguishing everyday observations from formal scientific inquiry.  Digital Media Impact: The text emphasizes that digital media profoundly affects identity, relationships, group dynamics, and health, illustrating how technology alters our interactions and perceptions. Cognitive Changes: The text discusses cognitive processes in the digital age, highlighting how technology can enhance or diminish cognitive functions such as attention, memory, and emotional regulation. Empathy and Social Behavior: It explores the role of empathy in shaping both pro-social and anti-social behaviors online, noting that a lack of empathy can lead to negative social interactions. Community Dynamics: The document outlines the impact of online behavior on real-world communities, detailing how digital interactions can foster both connection and division. Implications for Mental Health: The text addresses the psychological consequences of digital media use, indicating potential risks such as addiction, anxiety, and diminished social skills. Key Insights Psychological Foundations of Digital Media: The relationship between psychological theories and digital media is crucial for understanding how individuals navigate their online identities. Theories like the hyperpersonal model illustrate that online interactions can lead to idealized perceptions of others, affecting how we perceive and present ourselves in digital spaces. The lack of non-verbal cues in online communication can lead to increased self-presentation strategies, which may result in deeper connections but also in distortions of authentic identity. Cognitive Offloading and Memory: Digital technology facilitates cognitive offloading, where individuals rely on external devices to remember information rather than retaining it internally. This shift raises concerns about the long-term effects on memory retention and cognitive development, particularly among younger users who may lack the skills to memorize or process information deeply. The ease of accessing information online can diminish the need for meaningful engagement with content, leading to superficial understanding. Attention and Multitasking: The impact of digital media on attention is notable, with studies indicating that heavy multitaskers may perform worse in tasks that require sustained attention. The constant switching between tasks online can lead to fragmented attention spans, where users struggle to focus deeply on any one task. This phenomenon is complemented by the dopamine- driven nature of online interactions, where immediate rewards can become addictive, further straining cognitive capacities. Empathy in Digital Interactions: Empathy plays a dual role in online environments, influencing both pro-social and anti-social behaviors. The lack of face-to-face interaction can diminish empathetic responses, leading to behaviors such as trolling and cyberbullying. Conversely, digital platforms also enable expressions of empathy through supportive communities and shared experiences, fostering connection among users who may feel isolated in their offline lives. Social Identity and Group Dynamics: The text highlights how social identity theory applies to online interactions, where individuals often form in-groups and out-groups based on shared interests or beliefs. This segmentation can lead to polarization, where extreme viewpoints are amplified, and group cohesion is prioritized over constructive dialogue. Understanding these dynamics is essential for addressing online conflicts and fostering inclusive digital communities.  Mental Health Considerations: The implications of digital media for mental health are profound, with increased usage linked to issues such as anxiety, depression, and addiction. The text emphasizes the need for awareness of these risks, particularly among vulnerable populations like adolescents. Strategies for promoting healthy digital habits are essential for mitigating negative outcomes associated with excessive online engagement. Community Building vs. Isolation: Digital media has the potential to build communities that transcend geographical boundaries, allowing individuals to connect over shared interests. However, this can lead to echo chambers where dissenting opinions are marginalized. Striking a balance between fostering community and ensuring diversity of thought is vital for a healthy digital ecosystem. Conclusion The exploration of psychology in the context of digital media reveals significant insights into how technology influences human behavior, cognition, and social dynamics. Understanding these interactions is crucial for developing strategies that promote healthy online environments and mitigate the potential psychological risks associated with digital engagement. As digital media continues to evolve, ongoing research and education will be essential for navigating the complexities of our increasingly interconnected world. TRANSTHEORITCAL MODEL OF CHANGE Chapter: Understanding the Transtheoretical Model of Change Introduction The journey of transforming habits or behaviors is multifaceted and often riddled with challenges. The Transtheoretical Model (TTM), developed by psychologists James Prochaska and Carla DiClemente in the 1970s, serves as a roadmap for individuals seeking to make lasting changes in their lives. This model emphasizes that change is not a linear process but rather a series of stages that individuals must navigate. Each stage represents a different level of readiness for change, and understanding these stages can significantly enhance the likelihood of success. The TTM is particularly valuable for a variety of contexts, such as quitting smoking, adopting healthier lifestyles, or encouraging others to embrace positive changes. This chapter will explore the six stages of the Transtheoretical Model, offering insights into the psychological mechanisms at play, relevant case studies, and practical applications of the model in everyday life. The Stages of Change Stage 1: Pre-contemplation - Definition: In the pre-contemplation stage, individuals are often unaware of the need for change or believe that their actions are not detrimental. They may be resistant to the idea of change and downplay the positives of adopting new habits. - Key Characteristics: - Lack of awareness regarding the negative impact of current behaviors. - A tendency to overemphasize the cons of changing. - Individuals may be months away from contemplating a change. - Example: Someone might recognize that a vegan diet could lessen their carbon footprint but might dismiss the switch due to perceived high costs or the sacrifice of favorite foods. - Implications: To progress from this stage, self-reflection is crucial. Individuals need to confront their behaviors and acknowledge their consequences.  Stage 2: Contemplation - Definition: The contemplation stage is characterized by individuals acknowledging their problematic behaviors but feeling ambivalent about the change. They see the need for change but are held back by various fears or misconceptions. - Key Characteristics: - Understanding the harmful effects of current habits. - Potentially staying in this stage for months or years due to a skewed perception of change. - Example: Smokers may realize that smoking harms their health yet struggle with the idea of losing a social outlet and stress-relief mechanism. - Strategies for Progression: - Identify barriers to change. - Weigh the pros and cons more objectively. - Cultivate a mindset that focuses on the benefits of gaining new habits rather than the loss of old ones. Stage 3: Preparation - Definition: In the preparation stage, individuals are ready to take action within the next month. They may begin to make small changes and test the waters before fully committing to a significant behavioral shift. - Key Characteristics: - Understanding the benefits of the change. - Engaging in preliminary actions, such as reducing the number of cigarettes smoked. - Strategies for Success: - Developing SMART goals (Specific, Measurable, Achievable, Relevant, Time-bound). - Conducting research on potential obstacles and strategies to overcome them. - Creating alternative plans to adapt to unexpected challenges. Stage 4: Action - Definition: The action stage is where individuals actively engage in modifying their behaviors. This stage often requires significant effort and commitment. - Key Characteristics: - Individuals have made observable changes in their behavior. - The action stage typically lasts three to six months. - Challenges: - Encountering obstacles and potential relapses. - The importance of support systems and continuous preparation even after initiating action. - Example: A person who quits smoking cold turkey after watching an impactful documentary. - Implications for Success: Rewarding oneself for progress and maintaining motivation are critical during this phase. Stage 5: Maintenance - Definition: The maintenance stage is reached when individuals have successfully sustained their behavior change for at least six months. Confidence in their new habits typically increases, but vigilance remains essential. - Key Characteristics: - Awareness of potential temptations and strategies to avoid relapse. - The possibility of relapse is still present and should be acknowledged. - Strategies for Sustaining Change: - Continued self-reflection to recognize triggers for temptation.  - Developing a robust support network to help navigate challenges. Stage 6: Relapse - Definition: Relapse is a common occurrence in the process of behavior change, with rates for substance abuse ranging between 40% and 60%. It can happen even after prolonged periods of success. - Key Characteristics: - Individuals revert to previous behaviors. - Relapse is not a failure but an opportunity for learning and growth. - Strategies for Recovery: - Emphasizing self-compassion over self-shame. - Analyzing triggers that led to relapse and adjusting strategies accordingly. - Using insights from the earlier stages to re-engage in the model. Real-World Applications of the Transtheoretical Model - The TTM can be applied to various scenarios, from personal health changes to professional settings. For instance, in corporate wellness programs, understanding where employees stand in the stages of change can help tailor interventions that support their journey toward healthier lifestyles. Similarly, healthcare providers can use the model to design patient education and support strategies that align with each patient's readiness to change. Conclusion - The Transtheoretical Model of Change provides a structured framework for understanding the complex process of behavior modification. By recognizing the significance of each stage—from pre-contemplation to relapse—individuals can better navigate their paths toward positive change. Each step is crucial; the preparation and action phases are built on the foundations laid in the earlier stages, while the maintenance phase reinforces the new behaviors. - Acknowledging the inevitability of relapses and the need for recovery strategies can foster resilience and promote long-term success. The insights gained from the TTM not only empower individuals to change their habits but also enable them to support others in their journeys, creating a ripple effect of positive transformations in various aspects of life. Understanding and applying the principles of the Transtheoretical Model can lead to a healthier, more fulfilling life, underscoring the model's enduring relevance in the pursuit of personal growth and well-being. MAKOSWKI PERSUASION TECHNIQUES Notes on Major Techniques of Persuasion 1. Appeal to or Creation of Needs o Definition: Advertisers evoke or create a need and present their product as a solution. o Framework: Based on a modified version of Maslow's Hierarchy of Needs: ▪ Physiological Needs: Hunger, thirst, etc. (e.g., "Aren't you hungry for Burger King now?") ▪ Safety and Security Needs: Protection and stability (e.g., "Get a piece of the rock") ▪ Belongingness and Love Needs: Social acceptance (e.g., "Brush your breath with Dentyne") ▪ Self-Esteem and Status Needs: Recognition and respect (e.g., "When E.F. Hutton speaks...")  ▪ Cognitive Needs: Desire for knowledge (rare in ads) ▪ Aesthetic Needs: Appreciation of beauty (rare in ads) ▪ Self-Actualization Needs: Fulfilling potential (rare in ads) o Observation: Advertisers focus more on basic needs to appeal to a broader audience. 2. Social and Prestige Suggestion o Definition: Persuading consumers to act based on others' behaviors or endorsements. o Types: ▪ Social Suggestion: Encourages buying/doing X because "everyone else is doing it." ▪ Example: The Pepsi Generation, Wrigley's Spearmint Gum. ▪ Prestige Suggestion: Promotes products endorsed by famous or prestigious figures. ▪ Example: James Garner for Polaroid, Bill Cosby for Jello, celebrities for American Express. 3. Loaded Words and Images o Definition: Uses emotionally charged language and appealing visuals to influence decisions. o Techniques: ▪ Buzzwords: Words like "natural" (beauty products) and "light" (diet products). ▪ Attractive Imagery: Featuring athletic or attractive people (e.g., athletes eating Snickers). ▪ Product Image: Tailoring brand identity to target audiences. ▪ Michelob Beer: Social, couple-oriented settings (e.g., "Weekends were made for Michelob"). ▪ Budweiser Beer: Achievement-focused, male-oriented (e.g., "For all you do, this Bud's for you"). ▪ Suspending Reason: Associating unrelated imagery with products (e.g., cigarettes with outdoor scenes for a "fresh" taste). Summary: Advertisers effectively use the appeal to needs, social and prestige suggestions, and loaded words/images to persuade consumers. These techniques manipulate emotions, social dynamics, and perceptions to influence buying behavior. The Hyperpersonal Model of Mediated Communication at Twenty-Five Years by Joseph B. Walther and Monica T. Whitty 1. Core Concepts of the Hyperpersonal Model o Foundation in Social Information Processing (SIP) Theory: ▪ Communicators use available communicative codes (verbal or nonverbal) to convey socioemotional messages. ▪ In CMC, lacking nonverbal cues, users rely on text to express affect, personality, and identity. o Key Difference from SIP Theory: ▪ Hyperpersonal communication suggests that limited cues in CMC enhance intimacy rather than inhibit it. 2. Four Key Components (Berlo's Communication Model Applied to CMC)  o Sender: ▪ Engages in selective self-presentation—chooses desirable traits to display while concealing flaws. ▪ Can manipulate language, tone, and style to construct an idealized persona. o Receiver: ▪ Tends to idealize the sender, compensating for missing cues by filling in gaps with positive assumptions. ▪ Online self-disclosure is perceived as more intimate than in FtF interactions. o Channel: ▪ Asynchronous communication allows for strategic message crafting and editing. ▪ More time to reflect and compose intimate or optimized responses. o Feedback: ▪ Reciprocal feedback reinforces idealized perceptions (expectancy confirmation). ▪ Positive feedback leads senders to embody the desirable traits they've portrayed. 3. Boundaries and Contemporary Applications o Mono-Modal Contexts: ▪ Text-based social support groups foster intimate relationships (Turner et al., 2001). ▪ Text-based customer service interactions impact perceptions of agents and companies (Lew et al., 2018). ▪ Socially anxious individuals prefer text-based interactions for more rewarding social connections (High & Caplan, 2009). o Multi-Modal Contexts: ▪ Online role-playing games and dating sites blend text with visuals, amplifying hyperpersonal effects (Klimmt & Hartmann, 2008). ▪ Extended online interactions often lead to disappointment upon meeting in person due to heightened idealization (Ramirez et al., 2014). 4. Deceptive Online Interactions and Romance Scams o Intentional Exploitation of Hyperpersonal Dynamics: ▪ Romance scammers use idealized self-presentations and continuous communication to build trust and emotional attachment. ▪ Victims often ignore warnings due to strong emotional bonds reinforced by strategic feedback and manipulation. ▪ Techniques include using stolen photos, fabricated identities, and maintaining frequent, intimate contact. 5. Model Limitations and Adaptations o Warranting Theory: ▪ Verifiable online cues reduce self-enhancing distortions in serious relationship contexts (Walther & Parks, 2002). o Technological Affordances: ▪ Features like editing tools and social feedback systems (e.g., Likes) impact self- presentation strategies. 6. Social Performance at Scale o Performative Self-Presentation: ▪ Social media encourages curated personas for visible and imagined audiences (Baym & boyd, 2012). ▪ Moral grandstanding and outrage on social media can reflect deliberate self- presentation strategies (Grubbs et al., 2019). o Feedback Amplification: ▪ Likes and comments reinforce users' online identities, potentially altering self- perceptions (Sherman et al., 2018). o Negative Extensions: ▪ Hyperpersonal dynamics may also contribute to extremist group bonding and antisocial behaviors online.  7. Future Research Directions o Investigate hyperpersonal effects in large-scale social media interactions. o Explore cultural differences in online self-presentation and audience perception. o Study the role of multi-modal communication in shaping hyperpersonal relationships. Summary: The hyperpersonal model reveals how CMC can produce relationships that are more intimate and idealized than FtF interactions. Through selective self-presentation, idealized perceptions, channel affordances, and reinforcing feedback, users craft socially desirable personas. The model explains both positive and harmful online behaviors, including deception and social manipulation. Continued research is essential to understand its implications in evolving digital landscapes. Examining How and When Facebook Intensive Use Shapes Users' Online Pro-Social Behaviors 1. Core Concepts and Theoretical Framework Uses and Gratification Theory (UGT): o UGT explains how individuals actively use media to fulfill psychological and social needs, such as social interaction, self-confidence, emotional support, and information acquisition. o Facebook serves as a platform to meet these gratification needs, encouraging users to engage in behaviors that foster social connectedness. Online Pro-Social Behavior: o Defined as voluntary, online actions intended to benefit others and promote harmonious relationships. o Examples include sharing resources, offering compliments, supporting friends emotionally, and engaging positively in discussions. 2. Hypotheses and Proposed Model H1: Facebook intensive use is positively related to users' online pro-social behaviors. H2: Self-transcendence mediates the relationship between Facebook intensive use and online pro- social behaviors. H3: Online relationship commitment moderates the direct link between Facebook intensive use and self-transcendence and the indirect link between Facebook intensive use and online pro-social behavior. H4: Online relationship commitment moderates the indirect relationship between Facebook intensive use and online pro-social behavior via self-transcendence. 3. Key Constructs and Relationships Facebook Intensive Use: o Defined by frequent and emotionally involved interaction with Facebook to fulfill personal and social needs. Self-Transcendence: o Involves heightened environmental awareness and a broader life perspective. o Encourages altruism and empathy, fostering online pro-social behavior. o Acts as a mediator between Facebook use and pro-social behavior. Online Relationship Commitment: o Reflects users' belief in maintaining long-term online relationships. o Moderates the effect of Facebook use on self-transcendence and pro-social behaviors. 4. Methodology Participants: 467 university students from a large public sector university in Pakistan. Data Collection: Three-wave, time-lagged survey design over two months. Analysis: Structural Equation Modeling (SEM) using Mplus 8.5. Model Fit Indicators: χ²(588) = 1093.37, χ²/df = 1.85, RMSEA = 0.04, SRMR = 0.04, CFI = 0.95, TLI = 0.95. Validity Checks: Cronbach’s alpha > 0.70; AVE values > MSV and ASV, confirming convergent and discriminant validity. 5. Results  Direct Effect: Facebook intensive use significantly impacts online pro-social behaviors (B = 0.18, p <.01). Indirect Effect: Self-transcendence significantly mediates this relationship (B = 0.10, p <.01). Moderation Effect: Online relationship commitment strengthens the effect of Facebook use on self- transcendence (B = 0.13, p <.01). Moderated Mediation: Indirect effect via self-transcendence is significant for users with high relationship commitment (B = 0.15, p <.01). 6. Practical Implications Parental Guidance: Encourage positive Facebook use to promote empathy and altruism. Educational Strategies: Teachers can foster meaningful media engagement in students. Social Media Design: Platforms can incorporate features that nurture self-transcendence and pro- social engagement. 7. Contributions to Literature Highlights the positive role of Facebook in fostering pro-social behavior. Introduces self-transcendence as a mediating factor. Identifies online relationship commitment as a critical moderator. 8. Limitations and Future Research Causality Concerns: Reliance on self-reported data; future studies should adopt longitudinal designs. Cultural Context: Expand research across individualistic cultures for generalizability. Alternative Mediators: Investigate other factors (e.g., social capital) influencing pro-social behavior. Cross-Platform Comparison: Explore similar relationships on other social media platforms. 9. Conclusion Facebook intensive use promotes online pro-social behaviors, both directly and through self- transcendence. Online relationship commitment enhances this relationship, reinforcing the complex dynamics between Facebook use, psychological growth, and social engagement. Summary: This study affirms that Facebook intensive use fosters online pro-social behaviors, with stronger effects for users high in online relationship commitment. Self-transcendence plays a pivotal mediating role, providing deeper insights into how social media can cultivate positive, supportive online communities. Detailed Notes on "Framing Norms in Online Communities" by Koteswara Ivaturi and Cecil Chua 1. Core Concepts and Theoretical Framework Norm Formation in Online Communities: o Norms are informal, shared beliefs that guide routinized behavior, critical for governing online communities. o Online community leaders face a balance between enforcing norms and avoiding user disengagement. Frame Analysis Theory: o Adapted from social movements literature, frame analysis explains how moderators can influence norm formation. o Involves two key phenomena: Norm Acceptance and Norm Transience. ▪ Norm Acceptance: Requires consistent and credible communication from moderators. ▪ Norm Transience: Occurs when norms misalign with community identity, leading to their eventual rejection. 2. Hypotheses and Proposed Model Frame Construction: Moderators shape norms through diagnostic (problem identification), prognostic (solution proposing), and motivational (call to action) frames. Frame Interpretation: Effectiveness depends on frame credibility (consistency and empirical support) and salience (alignment with community identity). Model Outcome: Successful norm formation requires both high frame consistency and empirical credibility, while long-term adoption depends on salience with community identity. 3. Key Constructs and Relationships Frame Consistency: Alignment between moderators' stated beliefs and actions. Empirical Credibility: Evidence supporting the proposed norms (e.g., research, external validation). Frame Salience: Relevance and alignment of norms with community identity. 4. Methodology Case Analysis: Two online communities focused on recreational drug discussions (New Zealand and UK). Data Collection: Analysis of moderator-led threads and rich interactions over a span of years. Data Analysis: Identification of moderator-proposed norms, accepted norms, and transient norms using frame analysis. 5. Results Identified Moderator-Proposed Norms: 1. Prohibit drug sales on the community website. 2. Promote harm minimization strategies. 3. Discourage mixing different classes of drugs. 4. Standardize drug experience reporting. 5. Condemn intravenous drug use. 6. Discourage the use of acronyms like SWIM/SWIY. 7. Discuss techniques for passing drug tests. 8. Encourage conversations on drug legalization. 9. Warn against synthetic drugs being more dangerous than natural ones. Norm Acceptance Scenarios: o High Consistency & High Credibility: Norms were accepted (e.g., banning drug sales). o High Consistency & Low Credibility: Norms accepted despite weak evidence (e.g., discouraging intravenous drug use). o Low Consistency & High Credibility: Norms not accepted due to inconsistent moderator behavior. o Low Consistency & Low Credibility: Norms failed to form (e.g., drug legalization discussions). Norm Transience: o Use of SWIM/SWIY: Initially discouraged but later revived due to group identity alignment. o Synthetic vs. Natural Drugs: Initial acceptance eroded over time due to subgroup disagreements. 6. Practical Implications Moderator Strategies: o Maintain consistent communication and behavior. o Support claims with credible evidence. o Align norms with community identity for sustainability. Community Management: o Balance between informal influence and formal control. o Design norms to reflect the group’s shared values. 7. Contributions to Literature Extends frame analysis by demonstrating its application in online norm formation. Highlights the importance of consistency over empirical evidence in norm acceptance. Identifies the role of community identity in sustaining norms. 8. Limitations and Future Research Contextual Constraints: Findings based on recreational drug communities; generalizability may be limited. Temporal Dynamics: Longitudinal studies could better capture norm evolution. Additional Factors: Exploring other influences on norm sustainability (e.g., group dynamics). 9. Conclusion Successful norm formation in online communities requires consistent and credible framing by moderators.  Long-term norm sustainability depends on alignment with community identity. Moderators play a dual role as both enforcers and influencers, shaping community behavior through strategic framing. Summary: This study reveals that moderators can foster norms in online communities through consistent and credible framing. However, long-term sustainability of these norms hinges on their alignment with the community’s identity. The findings provide a framework for understanding how informal governance shapes user behavior in digital spaces. NOTES Comprehensive Summary of the Psychology of Digital Media Course Course Overview: This course explores the psychological foundations of digital media use, focusing on how digital environments shape behavior, identity, relationships, and mental health. It integrates theoretical knowledge with applied concepts in digital media, examining the interaction between users and digital technologies. 1. Key Psychological Concepts in Digital Media: Identity: o Online identity construction involves selective self-presentation (e.g., Instagram posts reflect curated aspects of the self). o Fragmentation of identity across different platforms due to context-specific behavior. Relationships: o Digital platforms reshape how relationships are formed and maintained. o Online interactions provide opportunities for introverts to express themselves more openly. Groups: o Online groups influence user behavior through group norms, conformity, and social identity. o Group polarization can lead to extreme opinions due to echo chambers. Health: o Digital media impacts mental health, with potential for both positive (social support) and negative (cyberbullying, anxiety) effects. 2. Characteristics of Digital Media (Lev Manovich): Numerical Representation: Digital content is encoded in binary code. Modularity: Media can be broken down into discrete components (e.g., text, images). Automation: Systems perform tasks automatically (e.g., photo enhancement). Variability: Digital content can be modified and remixed (e.g., memes). Transcoding: Fusion of digital and cultural layers, transforming content. Interactivity: Users engage with and contribute to digital content. 3. Theoretical Models in Digital Media Psychology: Uses and Gratification Theory (UGT): o Explains why individuals use media to satisfy psychological and social needs. o Highlights gratification from social connectedness, entertainment, and information. Hyperpersonal Model (Walther): o Online interactions enable selective self-presentation, leading to idealized perceptions. o Explains how CMC (computer-mediated communication) can sometimes surpass face-to- face communication in intimacy. Social Identity Model of Deindividuation Effects (SIDE): o Online anonymity can amplify social identity cues over personal identity, influencing behavior in group settings. Situated Action Theory: o Human behavior is context-dependent, influenced by material, social, and cultural factors. o Cognition is embodied and shaped by interactions with digital artifacts. 4. Digital Media and Group Dynamics: Group Formation and Influence: o Online groups form around shared interests, sometimes evolving into "zero-history" groups with no offline interaction.  o Group norms emerge through interaction and influence behavior. Conformity: o Online environments reduce conformity due to perceived anonymity. o Polarization occurs when users reinforce group-specific ideologies. Echo Chambers and Confirmation Bias: o Users gravitate towards like-minded communities, reinforcing beliefs. o This can lead to group polarization and extremism. 5. Persuasion in Digital Contexts: Elaboration Likelihood Model (ELM): o Central Route: Involves thoughtful processing of persuasive messages. o Peripheral Route: Relies on superficial cues (e.g., attractiveness, credibility). Electronic Word of Mouth (EWOM): o Online reviews and recommendations influence consumer behavior. o Credibility and similarity of reviewers enhance persuasive impact. Disinformation and Heuristics: o Disinformation spreads through heuristics like consistency, social proof, and authority. o Bots and fake profiles manipulate social proof to spread false information. 6. Online Relationships and Communication: Proximity and Similarity: o Online proximity (e.g., shared online spaces) fosters attraction. o Similarity in attitudes and interests strengthens online connections. Self-Disclosure: o Online anonymity encourages greater self-disclosure. o Higher levels of self-disclosure increase interpersonal attraction. Online Dating: o Platforms use algorithms (e.g., Tinder's Elo score) to match users. o Challenges include deception and "catfishing." 7. Digital Media and Mental Health: Positive Effects: o Access to social support and community engagement. Negative Effects: o Exposure to cyberbullying, social comparison, and disinformation. 8. Emotional Theories in Digital Contexts: Basic Emotion Theory (Ekman): Six universal emotions are expressed similarly across cultures. Schachter-Singer Two-Factor Theory: Emotions result from physiological arousal and cognitive appraisal. James-Lange Theory: Emotions stem from bodily responses. Cannon-Bard Theory: Emotions and physiological reactions occur simultaneously but independently. 9. Practical Applications: Social Media Design: Platforms can encourage positive behaviors (e.g., empathy) by shaping norms and features. Parental and Educational Guidance: Educating youth on healthy media use. Policy and Moderation: Implementing consistent and credible norms to govern online behavior. Conclusion: This course provided in-depth insights into the psychology of digital media, covering how digital environments influence identity, relationships, group behavior, and mental health. By integrating psychological theories and real-world applications, the course equips learners with the tools to critically analyze and engage with digital media in a mindful and informed manner. DICTIONARY Dictionary of Key Terms in the Psychology of Digital Media 1. Algorithm - A set of rules or processes used by digital platforms to deliver personalized content based on user behavior. 2. Anonymity - The ability to conceal one’s identity online, which can influence behavior and communication. 3. Automation - The use of technology to perform tasks with minimal human intervention. 4. Basic Emotion Theory - A theory proposing six universal emotions: happiness, sadness, fear, disgust, anger, and surprise. 5. Binary Code - The fundamental language of digital systems, consisting of 0s and 1s. 6. Bots - Automated programs designed to perform repetitive tasks online, often used for spreading information or spam. 7. Catfishing - Creating a fake online identity to deceive others, often in romantic contexts. 8. Central Route (ELM) - A path of persuasion involving careful and thoughtful consideration of message content. 9. Cognitive Appraisal - The process of interpreting and evaluating emotional stimuli. 10. Confirmation Bias - The tendency to seek and interpret information that confirms existing beliefs. 11. Context Collapse - The merging of multiple social contexts into one online platform, leading to audience ambiguity. 12. Cyberbullying - Harassment or bullying conducted through digital communication platforms. 13. Deindividuation - A psychological state where individuals lose self-awareness and engage in atypical behavior, often online. 14. Digital Footprint - The record of a user's online activities and interactions. 15. Digital Identity - The persona a user creates and manages across digital platforms. 16. Digital Literacy - The skills required to effectively and critically navigate digital environments. 17. Disinformation - False or misleading information spread deliberately to deceive. 18. Echo Chamber - An online environment where users are exposed only to information that aligns with their beliefs. 19. Electronic Word of Mouth (EWOM) - Online reviews and personal recommendations that influence consumer behavior. 20. Elo Score - A ranking system used by dating apps to match users based on perceived desirability. 21. Emotional Contagion - The spread of emotions through social networks. 22. Empirical Credibility - The perceived accuracy and reality of information based on observable evidence. 23. Frame Analysis - A method for understanding how information is structured to influence audience perception. 24. Frame Credibility - The trustworthiness and reliability of the message being framed. 25. Frame Salience - The relevance and importance of a framed message to its audience. 26. Group Conformity - Aligning one's behaviors or beliefs with those of a group. 27. Group Polarization - The tendency for group discussion to amplify the dominant opinion. 28. Heuristics - Mental shortcuts used to make quick judgments. 29. Hyperpersonal Model - A theory explaining how online communication can lead to more intimate relationships than face-to-face interactions. 30. Identity Cues - Signals that convey information about a person’s identity online. 31. Idealized Perception - Overly positive impressions formed in online interactions. 32. Information Overload - The difficulty of processing excessive amounts of information. 33. Interactivity - The degree to which users can participate in modifying content in real-time. 34. Memes - Cultural symbols or ideas transmitted digitally, often humorously. 35. Modularity - The design principle where digital content is composed of independent, interchangeable units. 36. Motivational Framing - Communication designed to inspire action. 37. Multimodal Communication - Communication that integrates various modes like text, images, and audio. 38. Narrative Framing - Structuring a story to shape interpretation and influence attitudes. 39. Norm Acceptance - The process by which a community embraces certain behaviors as standards. 40. Norm Transience - The temporary adoption of norms that do not align with community identity. 41. Online Disinhibition Effect - Reduced restraint in online interactions due to anonymity.  42. Online Pro-social Behavior - Positive actions online that benefit others, such as sharing helpful information. 43. Online Relationship Commitment - The dedication to maintaining relationships formed in digital spaces. 44. Parasocial Relationships - One-sided relationships where individuals feel connected to media personalities. 45. Peripheral Route (ELM) - Persuasion based on superficial cues rather than message content. 46. Persuasion Cues - Elements like authority or attractiveness used to influence opinions. 47. Psychographics - The study of personality, values, and interests in audience segmentation. 48. Reciprocity - Responding to positive actions with similar behavior. 49. Relational Aggression - Harmful behavior aimed at damaging relationships. 50. Selective Self-Presentation - Curating one’s online persona to control how others perceive them. 51. Self-Disclosure - Sharing personal information with others, often more openly online. 52. Self-Transcendence - Expanding personal concerns to focus on the welfare of others. 53. SIDE Model - Explains how anonymity enhances group conformity and social identity online. 54. Situated Action Theory - Emphasizes context and interaction in shaping behavior. 55. Social Capital - The value gained from social networks and relationships. 56. Social Comparison - Evaluating oneself relative to others. 57. Social Identity - A person’s sense of who they are based on group memberships. 58. Social Influence - How individuals change behavior due to others’ presence or opinions. 59. Social Integration - The process of becoming part of a social group. 60. Social Proof - Using others' behavior as a guide for one’s own actions. 61. Social Trust - Confidence in the integrity of others in social contexts. 62. Surveillance Capitalism - Monetizing personal data collected through digital surveillance. 63. Transcoding - Blending digital and cultural content. 64. Trolls - Users who intentionally provoke others online. 65. User-Generated Content (UGC) - Media created and shared by users. 66. Variability - Digital content’s ability to change and adapt. 67. Virality - The rapid spread of digital content. 68. Clickbait - Misleading content designed to attract clicks. 69. Filter Bubbles - Isolated information environments created by algorithms. 70. Gamification - Using game elements in non-game contexts. 71. Influencer Marketing - Promoting products through influential social media users. 72. Microtargeting - Using data to deliver personalized ads. 73. Selective Exposure - Seeking information that supports pre-existing views. 74. Technological Affordances - Features that enable specific user actions. 75. User Engagement - Interaction with digital content. 76. Digital Addiction - Compulsive use of digital devices. 77. Digital Well-being - Maintaining a healthy relationship with technology. 78. Fake News - False information presented as news. 79. Identity Performance - How individuals present themselves online. 80. Online Norms - Shared expectations of behavior in digital spaces. 81. Social Media Fatigue - Exhaustion from excessive social media use. 82. Surveillance - Monitoring online behavior. (Continued...) Conclusion: This glossary provides a comprehensive reference for key terms essential for understanding the psychology of digital media.