Intro to Communication Research Methods

Introduction to Communication Research

• Authority is knowledge gained from a trusted source, not direct experience.
• Communication researchers systematically study communication processes, effects, and contexts.
• Experience is knowledge gained through direct interaction or personal involvement.
• Hypotheses are testable statements predicting relationships between variables.
• Media research studies media content, audience impact, and media effects on society.
• Organizational communication studies how communication functions in organizations and businesses.
• Research is a systematic approach to discovering, interpreting, or revising knowledge.
• Scientific reasoning acquires knowledge through empirical evidence, logic, and systematic observation.
• Social research studies human behavior, social structures, and interactions.
• Tenacity is accepting something as true because it has always been believed.
• A theory is a structured explanation that predicts relationships between variables.
• Researchers develop research questions by identifying gaps in literature, observing real-world communication, and applying theoretical frameworks.
• Social research focuses on human behavior and interactions.
• Communication researchers study interpersonal relationships, media effects, and group communication.
• Humanities research explores meaning, culture, and historical perspectives through speeches, literature, or media.
• Critical and cultural research examines power dynamics, ideology, representation, and identity in communication.
• Academic research is distributed through peer-reviewed journals, books, conferences, public policy discussions, and media reports.
• The peer-review process includes manuscript submission, expert review, feedback, revision, and final approval for publication.
• Knowledge is gained through authority, personal experience, intuition, and tenacity, but these methods can be flawed.
• Scientific research is objective, systematic, replicable, and empirical, aiming to test hypotheses, establish theories, and generate reliable knowledge.

Research Perspectives and Paradigms

• Critical perspective examines power structures, inequalities, and communication's role in shaping realities.
• The deductive model begins with a theory, develops hypotheses, and collects data to test them.
• The inductive model begins with data collection and identifies patterns to develop a theory.
• Interpretivism emphasizes understanding human experiences and meanings, not objective truths.
• Positivism assumes an objective reality that can be measured using scientific methods.
• Proprietary research is conducted for private purposes, often by businesses, and is not publicly shared.
• Qualitative research explores meaning and human experiences through interviews, focus groups, and observations.
• Quantitative research collects numerical data to identify patterns and relationships between variables.
• Scholarly research is conducted for academic purposes and intended to contribute to public knowledge.
• Research paradigms are frameworks that guide research and include assumptions about reality, knowledge, and research methods.
• Common research paradigms include positivism, interpretivism, and critical research.
• Research paradigms are typically learned through academic training and exposure to research literature.
• Positivism assumes reality is objective and measurable; positivist researchers use experiments, surveys, and statistical analysis.
• Interpretivists believe reality is subjective and constructed through social interactions, using qualitative methods like interviews and case studies.
• The critical perspective challenges power structures and focuses on social change, analyzing media, discourse, and cultural narratives to reveal inequalities.
• Positivist methods examples: surveys, experiments, and statistical analysis.
• Interpretivist methods include ethnography, in-depth interviews, and focus groups.
• Critical methods include discourse analysis, media critique, and feminist analysis.
• Proprietary research is for private use, while scholarly research is published for public access and peer review.
• Scholarly research is peer-reviewed, replicable, and transparent (clearly explains methods and findings).
• The deductive model starts with a theory, develops hypotheses, and tests them with data, while the inductive model starts with observations, identifies patterns, and forms a theory.
• Qualitative: focuses on meaning and context, using interviews and observations
• Quantitative: focuses on numbers and patterns, using surveys and experiments.
• Qualitative research explores complex social phenomena.
• Quantitative research tests hypotheses and measures variables.

Research Questions, Objectives, and Hypotheses

• A research question guides an investigation by identifying the relationship between variables.
• A hypothesis is a testable statement predicting how variables relate to one another.
• The dependent variable (DV) is affected or measured in a study.
• The independent variable (IV) is manipulated or considered the cause in a study.
• A positive relationship means when one variable increases, the other also increases.
• A negative relationship means when one variable increases, the other decreases.
• A variable is a characteristic or factor that can change and can be measured using self-reports, observations, or physiological measures.
• The independent variable (IV) is the factor that is manipulated or influences changes.
• The dependent variable (DV) is the effect or outcome being measured.
• A research objective defines what a study aims to achieve.
• A research objective is a goal, while a research question is a specific inquiry.
• A hypothesis is a testable prediction about the relationship between variables.
• The hypothesis of association predicts two variables are related
• The causal hypothesis predicts that one variable causes another.
• Hypotheses should be testable and measurable, avoid vague language, and clearly define variables.

Variables

• Functions of Variables involves helping define relationships and test theories.
• Relationships Between Variables involves being correlated, causal, or unrelated.
• Measuring Variables occurs through self-report, observation, or physiological measures.
• Conceptual Definition is the general idea or abstract meaning of a concept.
• Operational Definition is how a concept is measured in a study.
• Conceptual Fit ensures the operational definition aligns with the conceptual definition.
• Extraneous Variables (Confounding Variables) involves being variables that unintentionally influence results.

Levels of Measurement:

• Nominal involves categories without ranking (e.g., gender).
• Ordinal involves ranked categories (e.g., education level).
• Interval involves Equal intervals with no true zero (e.g., temperature in Fahrenheit).
• Ratio involves equal intervals with a true zero (e.g., height, weight).
• Likert Scales are rating scales (e.g., “Strongly Agree” to “Strongly Disagree").
• Semantic Differential Scales involves measuring attitudes on bipolar adjectives (e.g., “Happy-Sad").
• Variables allow researchers to test relationships, analyze patterns, and make predictions.
• Conceptual definition defines what a term means
• Operational definition Defines how a term is measured.
• Conceptual fit ensures that the way we measure a concept aligns with its meaning.
• Triangulation combines multiple methods to increase accuracy.

Sampling

• Sampling Frame is the specific population from which a sample is drawn.
• Sampling Methods refers to the techniques used to select participants.
• Random Sampling means than every individual has an equal chance of selection.
• Non-Random Sampling means that some individuals have a higher chance of selection.
• Unit of Analysis is the subject being studied
• Response Rate/Refusal Rate refers to the percentage of people who participate/refuse.
• Sample Size is the number of participants included in a study.
• Data Saturation describes the point where additional data collection no longer provides new insights.
• Sampling is crucial because it determines how generalizable and valid the results are.
• A well-selected sample ensures findings can be applied to the larger population.
• Purposive Sampling involves selecting participants based on specific characteristics.
• Quota Sampling involves ensuring certain subgroups are represented.
• Snowball Sampling involves asking participants to recruit others.

Content Analysis

• Content analysis analyzes media and communication patterns.

Unitizing:

• Sampling Units refers to the materials studied
• Recording Units : The specific content being analyzed.
• Context Units Is the broader setting of the recording units.

Sampling in Content Analysis:

• Stratified Sampling involves dividing content into subgroups before sampling.
• Systematic Sampling involves the selection of every nth item from a list.
• Random Sampling involves selecting items at random.
• Reliability in Content Analysisinvolves ensuring coding decisions are consistent.
• Coding in Content Analysis involves categorizing content based on themes.
• Codebook is a guideline for coders to ensure consistency.
• Inter-Coder Reliability is an agreement between multiple coders.
• Intra-Coder Reliability shows the consistency of one coder over time.
• The three-legged stool of media effects research refers to surveys, experiments, and content analysis.
• Content analysis helps identify media trends, framing, and representation.
• Example research question: “How do news outlets frame climate change discussions?”

Explore communication research methods, emphasizing systematic study and empirical evidence. Learn about authority, experience, and scientific reasoning in research. Understand hypotheses, theories, and research types in media, organizations, and society.