[1J3-OS-10a] 大規模言語モデルとデータサイエンス

[1J3-OS-10a-03] Psychographic classifications of Reddit authors using the word-embedding technique

Travel sentiments and risk awareness of conservative and open-minded authors during the Covid-19 crisis

〇Gluckstad Kano Fumiko¹, Daniel Hardt¹ (1. Copenhagen Business School)

[[オンライン]]

キーワード：Psychographic classification, Risk awareness, Travel sentiment, Covid-19 crisis, Word-embedding

In this presentation, we highlight the methodological aspects of our latest work published in Tourism Management (https://doi.org/10.1016/j.tourman.2023.104821). In this work, we used over 1 million Reddit postings from January 2018 to January 2021, selected 3093 authors in three periods: 1. Before Covid 1, 2. Before Covid-2, 3. During Covid, and classified the authors based on psychological attributes for their posts in the first period. We created word vectors describing two psychographic characteristics: “openness to change" and "conservative" based on the Basic Human Values theory. By use of the word embedding technique, we classified these authors into the two groups by calculating semantic similarities between their postings during the first period and the two respective word vectors.
Our results showed that open-minded authors had more positive travel sentiment in the third period than conservative authors, while conservative authors increased risk awareness in the third period compared to open authors. Our study emphasizes that by classifying the authors of large-scale data based on psychological attributes, it is possible to predict the attitudes and behaviors that authors will express in the future, and that the application of theories in psychology and social sciences can deepen the insights obtained from large-scale data.