Predicting Swedish Elections with Twitter: A Case for Stochastic Link Structure Analysis

—The question that whether Twitter data can be leveraged to forecast outcome of the elections has always been of great anticipation in the research community. Existing research focuses on leveraging content analysis for positivity or negativity analysis of the sentiments of opinions expressed. This is while, analysis of link structure features of social networks underlying the conversation involving politicians has been less looked. The intuition behind such study comes from the fact that density of conversations about parties along with their respective members, whether explicit or implicit, should reflect on their popularity. On the other hand, dynamism of interactions, can capture the inherent shift in popularity of accounts of politicians. Within this manuscript we present evidence of how a well-known link prediction algorithm, can reveal an authoritative structural link formation within which the popularity of the political accounts along with their neighbourhoods, shows strong...

• Type: Journal
• Year: 2015
• Where: ASUNAM
• Authors: Nima Dokoohaki, Filippia Zikou, Daniel Gillblad, Mihhail Matskin
• Keywords: ASUNAM 2015, Social Networks