Twitter hashtags are typically used to categorize a tweet, to monitor ongoing conversations, and to facilitate accurate retrieval of posts. Hashtag hijacking occurs when a group of users starts using a trending hashtag to promote a topic that is substantially different from its recent context. Most of the prior research on hashtag hijacking has focused on manual monitoring of specific hashtags. We present a general framework based on multi-modal matrix factorization for automatically detecting hashtag hijacking from Twitter data, where the compromised hashtags and their underlying topics were unknown a priori. CCS Concepts•Security and privacy → Social engineering attacks; Intrusion/anomaly detection and malware mitigation;

Past research has suggested an associative relationship between social media use and alcohol consumption, especially among the younger generations. The current study takes a generalizable approach to examining the prevalence of posting about alcohol on a popular social media platform, Twitter, as well as examining the predictors of a tweet’s virality. We content-analyzed more than 47.5 million tweets that were posted in March 2015 to explore the prevalence of alcohol-related references, and how alcohol-related references, tweet features (e.g., inclusion of hashtags, pictures, etc.), and user characteristics (e.g., number of followers) contribute to the tweet’s virality. Our findings showed that during March 2015, about two of every 100 tweets in the United States were alcohol-related; whereas the majority of those referenced intoxication. In addition to tweet features and user characteristics, the prevalence of alcohol-related references in a tweet positively predicted the number of likes it received, yet negatively predicted the number of retweets. Given prior evidence supporting the association between social media use and alcohol consumption, the prevalence of alcohol references in tweets and how that contributes to their virality offers insights into the widespread phenomenon of glorifying alcohol use and excessive drinking via social media, pointing to potential negative health consequences.

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