Unveiling Emotional Dissemination in Hotspot Events: “Village Super League” Case Study
- DOI
- 10.2991/978-94-6463-276-7_42How to use a DOI?
- Keywords
- Big data; sentiment dissemination; online opinions; sports events; Village super league (Cun Chao)
- Abstract
The “Village Super League” sports event in Rongjiang, Guizhou, China, has emerged as a phenomenon with over 30 billion online views. This grassroots football tournament, organized spontaneously by local residents, has ignited widespread attention and discussions on social media platforms. Using big data techniques, this paper collects and analyzes textual data from users of both Weibo and TikTok, employing methods such as semantic network analysis and sentiment analysis. It delves into the mechanisms behind the dissemination of sentiment in hotspot events and the formation of online opinions, while probing into how the “Village Super” achieved its remarkable popularity and successful dissemination. This study contributes to a deeper understanding of the patterns governing mass sentiment dissemination in hotspot events and opens up fresh cognitive perspectives for studying the propagation of online events in the era of big data.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Jing Zhang AU - Guangquan Dai PY - 2023 DA - 2023/10/27 TI - Unveiling Emotional Dissemination in Hotspot Events: “Village Super League” Case Study BT - Proceedings of the 2023 4th International Conference on Big Data and Social Sciences (ICBDSS 2023) PB - Atlantis Press SP - 386 EP - 397 SN - 2667-128X UR - https://doi.org/10.2991/978-94-6463-276-7_42 DO - 10.2991/978-94-6463-276-7_42 ID - Zhang2023 ER -