Data Mining of the Concept "End of the World" in Twitter Microblogs

TL;DR

This study analyzes Twitter posts related to the 'end of the world' prediction, identifying frequent concept sets and association rules that could serve as early indicators of societal reactions to anticipated events.

Contribution

It introduces a method for detecting predictive markers in social media data through analysis of frequent sets and association rules related to specific topics.

Findings

Frequent sets peak before the predicted event with a time delay.

Association rule confidence dynamics show potential predictive signals.

Certain frequent sets serve as markers for societal anticipation.

Abstract

This paper describes the analysis of quantitative characteristics of frequent sets and association rules in the posts of Twitter microblogs, related to the discussion of "end of the world", which was allegedly predicted on December 21, 2012 due to the Mayan calendar. Discovered frequent sets and association rules characterize semantic relations between the concepts of analyzed subjects.The support for some fequent sets reaches the global maximum before the expected event with some time delay. Such frequent sets may be considered as predictive markers that characterize the significance of expected events for blogosphere users. It was shown that time dynamics of confidence of some revealed association rules can also have predictive characteristics. Exceeding a certain threshold, it may be a signal for the corresponding reaction in the society during the time interval between the maximum and probable coming of an event.