Cricket world cup 2015 : predicting user’s orientation through mix tweets on twitter platform

• Main Authors: Khatua, Apalak, Khatua, Aparup
• Other Authors: 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
• Format: Conference or Workshop Item
• Language: English
• Published: 2020
• Subjects: Library and information science::Libraries; Sports Analytics; Big Data
• Online Access: https://hdl.handle.net/10356/139023
• Institution: Nanyang Technological University

The existing literature has explored various latent attributes of Twitter users. It is worth noting that user classification research in the context of gender or the political domain is mostly binary in nature such as male-female or Republican-Democrat. Conversely, in multi-team contexts user classification is a not a binary task. Also, prior studies have mostly ignored tweets which mention more than one orientation (i.e. both Republican and Democrat-related keywords) within a tweet. We consider these tweets as mix tweets. We investigate the relationship between user classification (in a multi-team context) and user-level mix tweeting pattern. To test our proposed model, we have extracted 3.5 million tweets during the Cricket World Cup 2015 (CWC’15), in which 14 cricket-playing nations participated. We employed a logistic regression model, and our empirical evidence strongly confirms our hypothesis.