Predicting retweet count using visual cues

Autor: R. Manmatha, Ethem F. Can, Hüseyin Oktay
Rok vydání: 2013
Předmět:
Zdroj: CIKM
DOI: 10.1145/2505515.2507824
Popis: Social media platforms allow rapid information diffusion, and serve as a source of information to many of the users. Particularly, in Twitter information provided by tweets diffuses over the users through retweets. Hence, being able to predict the retweet count of a given tweet is important for understanding and controlling information diffusion on Twitter. Since the length of a tweet is limited to 140 characters, extracting relevant features to predict the retweet count is a challenging task. However, visual features of images linked in tweets may provide predictive features. In this study, we focus on predicting the expected retweet count of a tweet by using visual cues of an image linked in that tweet in addition to content and structure-based features.
Databáze: OpenAIRE