Social Media Data Analysis and Privacy Course Overview

Study Notes

The course covered post-conditions related to social media concerns, data collection, and privacy.
Students were expected to understand social media problems, data collection methods, and privacy implications.
The course emphasized the need to analyze social media concerns, solutions, and data collection instruments.
Slides from each week of the course were reviewed to prepare students for exams.
A movie called "Sully" was recommended for its relevance to crisis management using social media.
Social media's role in crisis management was discussed, citing examples like the Boston bombing and Twitter's impact.
Detailed analysis was conducted on social media data generation, volume, and the 4 V's - velocity, variety, volume, and veracity.
Importance of understanding Linux, Python, and data collection methods for social media analysis was highlighted.
Various social media APIs were explored for data collection and analysis, including Facebook and Twitter.
The course delved into topics like geolocation analysis, link farming, and strategies like phishing and link hijacking.
Privacy concerns on social media were discussed, including the implications of reading privacy policies and the economics behind it.
Analysis of link farmers showed that popular accounts like Barack Obama and Britney Spears were also involved in link farming.
The course aimed to equip students with the knowledge to analyze social media interactions, responses, and impact on decision-making.
Techniques like PageRank, CDF graphs, and node degree distribution were used to analyze social media data patterns.
Link farming patterns revealed that top link farmers had high in-degree compared to random samples.
Characteristics of link farmers included being popular, active users like bloggers and experts, aiming to increase social influence.
The course tackled issues like social capital, cloud influence (Klout), and the cost of privacy policy reading on websites.- Researchers are exploring how to make privacy policies easier for users to understand and comply with.
Nudges, such as picture nudges and sentiment nudges, are being developed to help users think before posting online.
Metrics used to evaluate the effectiveness of nudges include changes in privacy settings, post frequency, and topic sensitivity.
Semantic attacks aim to deceive users by creating a disparity between the system model and the mental model.
A study conducted phishing attacks by collecting personal information from social networks to demonstrate the risks.
Different departments and majors were analyzed to understand the impact of phishing attacks across various user groups.
Identity resolution involves finding connections between different social media handles or identities of the same user.
Methods like profile linking can help organizations better understand user behavior and improve targeting in advertisements.
Whisper, an anonymous social network, lacks strong ties between users and requires moderation to manage interactions effectively.
Machine learning, natural language processing, image analysis, and behavior analysis are recommended areas for further exploration in social media research.
The course aims to equip students with practical skills to analyze social media data and address emerging challenges like protecting school children online.

Description

This quiz covers the key topics discussed in a course on social media concerns, data collection, and privacy. It includes information on crisis management, social media APIs, link farming, privacy implications, social media interactions analysis, and emerging challenges. Students are expected to be familiar with techniques like PageRank, CDF graphs, semantic attacks, nudges, and identity resolution.