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HYPERLINKS IN THE TWITTERVERSE: ANALYZING THE URL USAGE IN SOCIAL MEDIA POSTS
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2024-05
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Computer and Information Science
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http://dx.doi.org/10.34944/dspace/10280
Abstract
An important means for disseminating information on social media platforms is by including URLs that point to external sources in user posts. In X, formally known as Twitter, we estimate that about 21% of the daily stream of English-language posts contain URLs. Given this prevalence, we assert that studying URLs in social media holds significant importance as they play a pivotal part in shaping the flow of information and influencing user behavior. Examining hyperlinked posts can help us gain valuable insights into online discourse and detect emerging trends. The first aspect of our analysis is the study of users' intentions behind including URLs in social media posts. We argue that gaining insights about the users' motivations for posting with URLs has multiple applications, including the appropriate treatment and processing of these posts in other tasks. Hence, we build a comprehensive taxonomy containing the various intentions behind sharing URLs on social media. In addition, we explore the labeling of intentions via the use of crowdsourcing. In addition to the intentions aspect of hyperlinked posts, we analyze their structure relative to the content of the web documents pointed to by the URLs. Hence, we define, and analyze the segmentation problem of hyperlinked posts and develop an effective algorithm to solve it. We show that our solution can benefit sentiment analysis on social media. In the final aspect of our analysis, we investigate the emergence of news outlets posing as local sources, known as "pink slime", and their spread on social media. We conduct a comprehensive study investigating hyperlinked posts featuring pink slime websites. Through our analysis of the patterns and origins of posts, we discover and extract syntactical features and utilize them for developing a classification approach to detect such posts. Our approach has achieved an accuracy rate of 92.5%.
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