Finding Tipping Points in Web Text Data
Shoichiro Hara, Frey Urszula Ann, Shinsuke Mori, Masami Matsuda · 2023
With the spread of the Internet, large volumes of text data related to local communities or societies are being distributed on the Web, and the texts’ contents change significantly with large-scale disasters, political changes, or national elections, among others. If we can estimate the moments at which the texts’ contents change, we can consider that it indicates the possibility that some change occurred in society. Based on the above, this paper explores a new direction for area studies based on informatics compatible with the Internet age to detect Tipping Points in areas.