We feel fine and searching the emotional web
Proceedings of the fourth ACM international conference on Web search and data mining
Tweeting is believing?: understanding microblog credibility perceptions
Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work
Profanity use in online communities
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Fast learning for sentiment analysis on bullying
Proceedings of the First International Workshop on Issues of Sentiment Discovery and Opinion Mining
Self-disclosure and relationship strength in Twitter conversations
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2
Detecting offensive tweets via topical feature discovery over a large scale twitter corpus
Proceedings of the 21st ACM international conference on Information and knowledge management
Harnessing Twitter "Big Data" for Automatic Emotion Identification
SOCIALCOM-PASSAT '12 Proceedings of the 2012 ASE/IEEE International Conference on Social Computing and 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust
Tweets are forever: a large-scale quantitative analysis of deleted tweets
Proceedings of the 2013 conference on Computer supported cooperative work
| Hi-index | 0.00 |
Cursing is not uncommon during conversations in the physical world: 0.5% to 0.7% of all the words we speak are curse words, given that 1% of all the words are first-person plural pronouns (e.g., we, us, our). On social media, people can instantly chat with friends without face-to-face interaction, usually in a more public fashion and broadly disseminated through highly connected social network. Will these distinctive features of social media lead to a change in people's cursing behavior? In this paper, we examine the characteristics of cursing activity on a popular social media platform - Twitter, involving the analysis of about 51 million tweets and about 14 million users. In particular, we explore a set of questions that have been recognized as crucial for understanding cursing in offline communications by prior studies, including the ubiquity, utility, and contextual dependencies of cursing.