SOLO: A Corpus of Tweets for Examining the State of Being Alone
June 04, 2020 ยท Declared Dead ยท ๐ International Conference on Language Resources and Evaluation
"No code URL or promise found in abstract"
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Authors
Svetlana Kiritchenko, Will E. Hipson, Robert J. Coplan, Saif M. Mohammad
arXiv ID
2006.03096
Category
cs.CL: Computation & Language
Cross-listed
cs.CY
Citations
7
Venue
International Conference on Language Resources and Evaluation
Last Checked
5 months ago
Abstract
The state of being alone can have a substantial impact on our lives, though experiences with time alone diverge significantly among individuals. Psychologists distinguish between the concept of solitude, a positive state of voluntary aloneness, and the concept of loneliness, a negative state of dissatisfaction with the quality of one's social interactions. Here, for the first time, we conduct a large-scale computational analysis to explore how the terms associated with the state of being alone are used in online language. We present SOLO (State of Being Alone), a corpus of over 4 million tweets collected with query terms 'solitude', 'lonely', and 'loneliness'. We use SOLO to analyze the language and emotions associated with the state of being alone. We show that the term 'solitude' tends to co-occur with more positive, high-dominance words (e.g., enjoy, bliss) while the terms 'lonely' and 'loneliness' frequently co-occur with negative, low-dominance words (e.g., scared, depressed), which confirms the conceptual distinctions made in psychology. We also show that women are more likely to report on negative feelings of being lonely as compared to men, and there are more teenagers among the tweeters that use the word 'lonely' than among the tweeters that use the word 'solitude'.
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