Twitter Topic Evolution/Information Diffusion Research
Paper Reads and Summary
Y. Yang
21/12/2015
Agenda
- An Analysis of Topical Proximity in the Twitter Social Graph
- Predicting the Speed, Scale, and Range of Information Diffusion in Twitter
- Differences in the Mechanics of Information Diffusion Across Topics: Idioms, Political Hashtags, and Complex Contagion on Twitter
University College Dublin, UCSB
The relationship between content similarity and social distance in the social network
Investigated the utility of prominent features such as Retweets and Hashtags as predictors of similarity
We aim to test whether and to which extent distance in a social network correlates with content similarity.
What is good
assess two types of signals per user independently, with respect to both of their roles as target and source of feedback respectively, while processing feedback events in their temporal order, not only the quality of the user as content creator is evaluated, but also the quality of the user as a content evaluator
real-world user relationships has been highlighted as an important factor to leverage improved recommendation quality. For instance, modeling the reputation of users to bias future recommendations from users who are both relevant and reputable
What is good
