In this post I want to pull together a couple of ideas around some of the measurable user activity generated as part of CFHE12. This will mainly focus around Twitter with some data from blog posts. I conclude that there are some simple opportunities to incorporate data from twitter into other channels, for example, summary of questions and retweets.
Truthy is a research project that helps you understand how memes spread online. We collect tweets from Twitter and analyze them. With our statistics, images, movies, and interactive data, you can explore these dynamic networks.
Our first application was the study of astroturf campaigns in elections. Currently, we're extending our focus to several themes. Browse the collection on the Memes page. Check out the Movie tool to browse and create animations of meme networks.
S. Rosenthal, N. Farra, и P. Nakov. (2019)cite arxiv:1912.00741Comment: sentiment analysis, Twitter, classification, quantification, ranking, English, Arabic.
D. Tang, F. Wei, N. Yang, M. Zhou, T. Liu, и B. Qin. Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), стр. 1555--1565. Baltimore, Maryland, Association for Computational Linguistics, (июня 2014)
M. McCord, и M. Chuah. Proceedings of the 8th International Conference on Autonomic and Trusted Computing, стр. 175--186. Berlin, Heidelberg, Springer-Verlag, (2011)
Y. Duan, L. Jiang, T. Qin, M. Zhou, и H. Shum. Proceedings of the 23rd International Conference on Computational Linguistics, стр. 295--303. Stroudsburg, PA, USA, Association for Computational Linguistics, (2010)