Sentiment analysis of tweets on alopecia areata, hidradenitis suppurativa, and psoriasis: Revealing the patient experience
BackgroundChronic dermatologic disorders can cause significant emotional distress. Sentiment analysis of disease-related tweets helps identify patients’ experiences of skin disease.ObjectiveTo analyze the expressed sentiments in tweets related to alopecia areata (AA), hidradenitis suppurativa (HS),...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-10-01
|
| Series: | Frontiers in Medicine |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmed.2022.996378/full |
| _version_ | 1811245958477905920 |
|---|---|
| author | Irene Tai-Lin Lee Sin-Ei Juang Steven T. Chen Christine Ko Christine Ko Kevin Sheng-Kai Ma Kevin Sheng-Kai Ma Kevin Sheng-Kai Ma Kevin Sheng-Kai Ma |
| author_facet | Irene Tai-Lin Lee Sin-Ei Juang Steven T. Chen Christine Ko Christine Ko Kevin Sheng-Kai Ma Kevin Sheng-Kai Ma Kevin Sheng-Kai Ma Kevin Sheng-Kai Ma |
| author_sort | Irene Tai-Lin Lee |
| collection | DOAJ |
| description | BackgroundChronic dermatologic disorders can cause significant emotional distress. Sentiment analysis of disease-related tweets helps identify patients’ experiences of skin disease.ObjectiveTo analyze the expressed sentiments in tweets related to alopecia areata (AA), hidradenitis suppurativa (HS), and psoriasis (PsO) in comparison to fibromyalgia (FM).MethodsThis is a cross-sectional analysis of Twitter users’ expressed sentiment on AA, HS, PsO, and FM. Tweets related to the diseases of interest were identified with keywords and hashtags for one month (April, 2022) using the Twitter standard application programming interface (API). Text, account types, and numbers of retweets and likes were collected. The sentiment analysis was performed by the R “tidytext” package using the AFINN lexicon.ResultsA total of 1,505 tweets were randomly extracted, of which 243 (16.15%) referred to AA, 186 (12.36%) to HS, 510 (33.89%) to PsO, and 566 (37.61%) to FM. The mean sentiment score was −0.239 ± 2.90. AA, HS, and PsO had similar sentiment scores (p = 0.482). Although all skin conditions were associated with a negative polarity, their average was significantly less negative than FM (p < 0.0001). Tweets from private accounts were more negative, especially for AA (p = 0.0082). Words reflecting patients’ psychological states varied in different diseases. “Anxiety” was observed in posts on AA and FM but not posts on HS and PsO, while “crying” was frequently used in posts on HS. There was no definite correlation between the sentiment score and the number of retweets or likes, although negative AA tweets from public accounts received more retweets (p = 0.03511) and likes (p = 0.0228).ConclusionThe use of Twitter sentiment analysis is a promising method to document patients’ experience of skin diseases, which may improve patient care through bridging misconceptions and knowledge gaps between patients and healthcare professionals. |
| first_indexed | 2024-04-12T14:47:06Z |
| format | Article |
| id | doaj.art-4abaaf519aea418db40530ae362268ae |
| institution | Directory Open Access Journal |
| issn | 2296-858X |
| language | English |
| last_indexed | 2024-04-12T14:47:06Z |
| publishDate | 2022-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Medicine |
| spelling | doaj.art-4abaaf519aea418db40530ae362268ae2022-12-22T03:28:36ZengFrontiers Media S.A.Frontiers in Medicine2296-858X2022-10-01910.3389/fmed.2022.996378996378Sentiment analysis of tweets on alopecia areata, hidradenitis suppurativa, and psoriasis: Revealing the patient experienceIrene Tai-Lin Lee0Sin-Ei Juang1Steven T. Chen2Christine Ko3Christine Ko4Kevin Sheng-Kai Ma5Kevin Sheng-Kai Ma6Kevin Sheng-Kai Ma7Kevin Sheng-Kai Ma8Department of Radiology, Far Eastern Memorial Hospital, New Taipei City, TaiwanDepartment of Anesthesiology, College of Medicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University, Kaohsiung, TaiwanDepartment of Dermatology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, United StatesDepartment of Dermatology, Yale University, New Haven, CT, United StatesDepartment of Pathology, Yale University, New Haven, CT, United StatesDepartment of Dermatology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, United StatesCenter for Global Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United StatesDepartment of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United StatesCollege of Electrical Engineering and Computer Science, Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, TaiwanBackgroundChronic dermatologic disorders can cause significant emotional distress. Sentiment analysis of disease-related tweets helps identify patients’ experiences of skin disease.ObjectiveTo analyze the expressed sentiments in tweets related to alopecia areata (AA), hidradenitis suppurativa (HS), and psoriasis (PsO) in comparison to fibromyalgia (FM).MethodsThis is a cross-sectional analysis of Twitter users’ expressed sentiment on AA, HS, PsO, and FM. Tweets related to the diseases of interest were identified with keywords and hashtags for one month (April, 2022) using the Twitter standard application programming interface (API). Text, account types, and numbers of retweets and likes were collected. The sentiment analysis was performed by the R “tidytext” package using the AFINN lexicon.ResultsA total of 1,505 tweets were randomly extracted, of which 243 (16.15%) referred to AA, 186 (12.36%) to HS, 510 (33.89%) to PsO, and 566 (37.61%) to FM. The mean sentiment score was −0.239 ± 2.90. AA, HS, and PsO had similar sentiment scores (p = 0.482). Although all skin conditions were associated with a negative polarity, their average was significantly less negative than FM (p < 0.0001). Tweets from private accounts were more negative, especially for AA (p = 0.0082). Words reflecting patients’ psychological states varied in different diseases. “Anxiety” was observed in posts on AA and FM but not posts on HS and PsO, while “crying” was frequently used in posts on HS. There was no definite correlation between the sentiment score and the number of retweets or likes, although negative AA tweets from public accounts received more retweets (p = 0.03511) and likes (p = 0.0228).ConclusionThe use of Twitter sentiment analysis is a promising method to document patients’ experience of skin diseases, which may improve patient care through bridging misconceptions and knowledge gaps between patients and healthcare professionals.https://www.frontiersin.org/articles/10.3389/fmed.2022.996378/fullsentiment analysisTwitteralopecia areatahidradenitis suppurativapsoriasismental health |
| spellingShingle | Irene Tai-Lin Lee Sin-Ei Juang Steven T. Chen Christine Ko Christine Ko Kevin Sheng-Kai Ma Kevin Sheng-Kai Ma Kevin Sheng-Kai Ma Kevin Sheng-Kai Ma Sentiment analysis of tweets on alopecia areata, hidradenitis suppurativa, and psoriasis: Revealing the patient experience Frontiers in Medicine sentiment analysis alopecia areata hidradenitis suppurativa psoriasis mental health |
| title | Sentiment analysis of tweets on alopecia areata, hidradenitis suppurativa, and psoriasis: Revealing the patient experience |
| title_full | Sentiment analysis of tweets on alopecia areata, hidradenitis suppurativa, and psoriasis: Revealing the patient experience |
| title_fullStr | Sentiment analysis of tweets on alopecia areata, hidradenitis suppurativa, and psoriasis: Revealing the patient experience |
| title_full_unstemmed | Sentiment analysis of tweets on alopecia areata, hidradenitis suppurativa, and psoriasis: Revealing the patient experience |
| title_short | Sentiment analysis of tweets on alopecia areata, hidradenitis suppurativa, and psoriasis: Revealing the patient experience |
| title_sort | sentiment analysis of tweets on alopecia areata hidradenitis suppurativa and psoriasis revealing the patient experience |
| topic | sentiment analysis alopecia areata hidradenitis suppurativa psoriasis mental health |
| url | https://www.frontiersin.org/articles/10.3389/fmed.2022.996378/full |
| work_keys_str_mv | AT irenetailinlee sentimentanalysisoftweetsonalopeciaareatahidradenitissuppurativaandpsoriasisrevealingthepatientexperience AT sineijuang sentimentanalysisoftweetsonalopeciaareatahidradenitissuppurativaandpsoriasisrevealingthepatientexperience AT steventchen sentimentanalysisoftweetsonalopeciaareatahidradenitissuppurativaandpsoriasisrevealingthepatientexperience AT christineko sentimentanalysisoftweetsonalopeciaareatahidradenitissuppurativaandpsoriasisrevealingthepatientexperience AT christineko sentimentanalysisoftweetsonalopeciaareatahidradenitissuppurativaandpsoriasisrevealingthepatientexperience AT kevinshengkaima sentimentanalysisoftweetsonalopeciaareatahidradenitissuppurativaandpsoriasisrevealingthepatientexperience AT kevinshengkaima sentimentanalysisoftweetsonalopeciaareatahidradenitissuppurativaandpsoriasisrevealingthepatientexperience AT kevinshengkaima sentimentanalysisoftweetsonalopeciaareatahidradenitissuppurativaandpsoriasisrevealingthepatientexperience AT kevinshengkaima sentimentanalysisoftweetsonalopeciaareatahidradenitissuppurativaandpsoriasisrevealingthepatientexperience |