 |
This month: August 2021 A spatiotemporal approach for social media sentiment analysis The rapid growth of user-generated unstructured data through social media has raised several challenges and research opportunities. These data constitute a rich source of information for sentiment analysis and help an understanding of spontaneously expressed opinions. In this paper, a spatiotemporal sentiment analysis technique is formalized and applied to a case study of tweets about the FIFA 2014 World Cup. This approach exploits the summarization of sentiment analysis using the spatial and temporal dimensions and automatically generates opinion change flow maps through both dimensions. The results enable the tracking of opinion change flow maps through spatial and temporal analysis. |
 |
Also this month Breaching perpetual contact: Withdrawing from mobile and social media use in everyday life This qualitative study aimed to investigate the norms and daily practices around mobile and social technology by examining what happens when mobile phones and social media on any devices are removed from one’s daily life. Most studies on technology non-use focus on one device or platform. In this study, participants (N = 78) relinquished not only social media but also their mobile phones for a 10-day period, and made observations on their experiences before, during, and after the “withdrawal.” Participants initially experienced guilt and anxiety over violating a social contract by not being available and reachable anytime and anywhere, but mostly found their social capital — particularly bonding social capital — reinforced through the withdrawal. On the personal front, participants (re)discovered certain “life skills” like memory, imagination, and creativity in navigating their physical world and spending their time. |
