What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
Networks, Crowds, and Markets: Reasoning About a Highly Connected World
Networks, Crowds, and Markets: Reasoning About a Highly Connected World
Proceedings of the 20th international conference on World wide web
What's in a hashtag?: content based prediction of the spread of ideas in microblogging communities
Proceedings of the fifth ACM international conference on Web search and data mining
Characterizing the effectiveness of twitter hashtags to detect and track online population sentiment
CHI '12 Extended Abstracts on Human Factors in Computing Systems
Expert Systems with Applications: An International Journal
Learning to explore spatio-temporal impacts for event evaluation on social media
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part II
Re-tweeting from a linguistic perspective
LSM '12 Proceedings of the Second Workshop on Language in Social Media
Spatial influence vs. community influence: modeling the global spread of social media
Proceedings of the 21st ACM international conference on Information and knowledge management
Discover breaking events with popular hashtags in twitter
Proceedings of the 21st ACM international conference on Information and knowledge management
Is news sharing on Twitter ideologically biased?
Proceedings of the 2013 conference on Computer supported cooperative work
Generalized scale independence through incremental precomputation
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Spatio-temporal dynamics of online memes: a study of geo-tagged tweets
Proceedings of the 22nd international conference on World Wide Web
Spatio-temporal meme prediction: learning what hashtags will be popular where
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Tweeting under pressure: analyzing trending topics and evolving word choice on sina weibo
Proceedings of the first ACM conference on Online social networks
Twitter n-gram corpus with demographic metadata
Language Resources and Evaluation
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Hashtags are used in Twitter to classify messages, propagate ideas and also to promote specific topics and people. In this paper, we present a linguistic-inspired study of how these tags are created, used and disseminated by the members of information networks. We study the propagation of hashtags in Twitter grounded on models for the analysis of the spread of linguistic innovations in speech communities, that is, in groups of people whose members linguistically influence each other. Differently from traditional linguistic studies, though, we consider the evolution of terms in a live and rapidly evolving stream of content, which can be analyzed in its entirety. In our experimental results, using a large collection crawled from Twitter, we were able to identify some interesting aspects -- similar to those found in studies of (offline) speech -- that led us to believe that hashtags may effectively serve as models for characterizing the propagation of linguistic forms, including: (1) the existence of a "preferential attachment process", that makes the few most common terms ever more popular, and (2) the relationship between the length of a tag and its frequency of use. The understanding of formation patterns of successful hashtags in Twitter can be useful to increase the effectiveness of real-time streaming search algorithms.