Quantifying Collective Emotions: Japan's Societal Trends Through Enhanced Sentiment Index Using POMS2 and SNS

TL;DR

This paper develops an enhanced sentiment index using SNS data and POMS2 to quantify and analyze societal emotions in Japan, demonstrating consistency with previous blog-based studies and offering a new tool for visualizing societal trends.

Contribution

The study introduces a novel emotion index based on SNS data with an added 'Friendliness' indicator, improving the measurement of collective emotions in Japanese society.

Findings

The index aligns with previous blog-based emotion studies.

The methodology effectively captures societal emotional fluctuations.

The index can visualize societal trends over time.

Abstract

In this study, we constructed an emotion index that quantitatively represents the collective emotions present in the Japanese web space by utilizing Social Networking Service (SNS) post data. Building upon previous research that used blog data and the Profile of Mood States (POMS), we restructured the methodology using posts from X (formerly Twitter) and updated the model by adding the ``Friendliness" indicator from the POMS2 metrics. Through periodic and trend analyses of the emotional indicators derived from X's post data, we found that the extension is consistent with results previously reported using blog data. This suggests that our methodology effectively captures typical emotional fluctuations in Japanese society, independent of specific SNS platforms, and is expected to serve as an index to visualize societal trends.