Tighe PJ, Goldsmith RC, Gravenstein M, Bernard HR, Fillingim RB. The painful tweet: text, sentiment, and community structure analyses of tweets pertaining to pain.
J Med Internet Res 2015;
17:e84. [PMID:
25843553 PMCID:
PMC4400316 DOI:
10.2196/jmir.3769]
[Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2014] [Revised: 12/17/2014] [Accepted: 01/21/2015] [Indexed: 01/22/2023] Open
Abstract
Background
Despite the widespread popularity of social media, little is known about the extent or context of pain-related posts by users of those media.
Objective
The aim was to examine the type, context, and dissemination of pain-related tweets.
Methods
We used content analysis of pain-related tweets from 50 cities to unobtrusively explore the meanings and patterns of communications about pain. Content was examined by location and time of day, as well as within the context of online social networks.
Results
The most common terms published in conjunction with the term “pain” included feel (n=1504), don’t (n=702), and love (n=649). The proportion of tweets with positive sentiment ranged from 13% in Manila to 56% in Los Angeles, CA, with a median of 29% across cities. Temporally, the proportion of tweets with positive sentiment ranged from 24% at 1600 to 38% at 2400, with a median of 32%. The Twitter-based social networks pertaining to pain exhibited greater sparsity and lower connectedness than did those social networks pertaining to common terms such as apple, Manchester United, and Obama. The number of word clusters in proportion to node count was greater for emotion terms such as tired (0.45), happy (0.43), and sad (0.4) when compared with objective terms such as apple (0.26), Manchester United (0.14), and Obama (0.25).
Conclusions
Taken together, our results suggest that pain-related tweets carry special characteristics reflecting unique content and their communication among tweeters. Further work will explore how geopolitical events and seasonal changes affect tweeters’ perceptions of pain and how such perceptions may affect therapies for pain.
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