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Study, 2025

What do people say about PMS and PMDD on social media, and is it positive or negative?

An analysis of tweets on X (formerly Twitter) found that tweets about PMDD were more negative in tone than tweets about PMS, with both using emotionally charged language.

Early or limited evidence Top 100 tweets using 'PMS' and top 100 tweets using 'PMDD' on X platform

What they did

Researchers collected the 100 most popular tweets for each of the search terms 'PMS' and 'PMDD' on X. They analyzed the language using two different sentiment analysis tools and identified the most frequently used words.

What they found

Tweets about PMDD had an overall negative sentiment rating of -24.3. The most frequently appearing words in PMDD tweets were 'month' (17 times), 'bad' (16 times), 'love' (15 times), 'feel' (14 times), 'MAFS' (14 times), and 'support' (14 times). Tweets about PMS had a sentiment rating of -15.2, which is less negative. The most frequently appearing words in PMS tweets were 'new' (11 times), 'price' (10 times), 'oxford' (9 times), 'feel' (14 times), 'people' (9 times), and 'want' (9 times).

What it means for you

People on social media discuss PMDD with more negative language than PMS, which may reflect how seriously people view PMDD. The main limitation is that this only analyzes tweets and does not represent all people's views or actual medical understanding.

-24.3

sentiment rating for PMDD tweets

-15.2

sentiment rating for PMS tweets

100

top tweets analyzed for each search term

About the study

Original title
Chirps and Sentiments regarding PMS and PMDD: where does X stand?
Authors
Noureddine C, Alvim de Paula G, Sterchele A
Journal
European psychiatry : the journal of the Association of European Psychiatrists
Year
2025
Study design
Study
What was tested
None
Open access
Yes
Original abstract

Introduction The emergence of social media platforms like X has created a unique space for mental health discussions. This study aims to analyze the language and themes used in social media discussions to appreciate sentiments about PMS and PMDD by looking at a sample of the most popular tweets on platform X. Objectives We hypothesize that this content can provide insight into public perceptions and guide educational campaigns. Methods An advanced Twitter/X search for “PMS” and “PMDD” was conducted, filtering for English content. The top 100 tweets for each search term were explored through two different sentiment analysis tools which include Dr. Daniel Soper’s Sentiment Analyzer Tool and Text2Data Application Programming Interface (API) Natural Language Processing (NLP) Analysis. Tweets were also analyzed using a word cloud generator to identify the most frequently used terms. Connecting words were eliminated from the final output. Results Negative sentiment was more prevalent than positive among the tweets for PMDD, with an overall sentiment analysis of an average of -24.3 per the Daniel Soper Sentiment Analyzer tool, suggesting a negative and serious tone. The most frequently appearing terms in these tweets were “month” (mentioned 17 times), “bad” (16), “love” (15), “feel” (14), “MAFS” (14), “support (14). Per Text2Data’s API NLP analysis, the top 150 words had a negative sentiment of -0.59 with a magnitude of 1.69. Negative sentiment was more prevalent than positive among the tweets for PMS, with an overall sentiment analysis of an average of -15.2 per the Daniel Soper Sentiment Analyzer tool, suggesting a somewhat negative and serious tone. The most frequently appearing terms in these tweets were “new” (11), “price” (10), “oxford” (9), “feel” (14), “people” (9), “want” (9). Per Text2Data’s API NLP analysis, the top 150 words had neutral sentiment of +0.15 with a magnitude of 1.59. Conclusions This study emphasizes a less negative sentiment associated with PMS compared to PMDD. It also highlights how more emotionally charged terms were used among tweets discussing PMDD compared to PMS. This may reflect public perception of the two conditions. Additionally, social media can be a way to gauge public interest and perception of medical topics. Disclosure of Interest None Declared

Reproduced under CC-BY.

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