Predicting political sentiments of voters from Twitter in multi-party contexts

• Main Authors: Khatua, Aparup, Khatua, Apalak, Cambria, Erik
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Computer science and engineering; Political Learning; Multi-party Context
• Online Access: https://hdl.handle.net/10356/155267
• Institution: Nanyang Technological University

Prior Twitter-based electoral research has mostly ignored multi-party contexts and ‘mix tweets’ that jointly mention more than one party. Hence, we investigate the complex nature of these mix tweets in a multi-party context, and we argue mix tweeting patterns of users implicitly capture their politi...