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Diabetes on Twitter: A Sentiment Analysis.

Elia Gabarron1, Enrique Dorronzoro2, Octavio Rivera-Romero2

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Journal of Diabetes Science and Technology
|November 21, 2018
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Summary
This summary is machine-generated.

Social media sentiment analysis reveals that tweets about diabetes, particularly T2D, can be more negative, especially without emojis. Emojis often correlate with more positive sentiment in diabetes discussions online.

Keywords:
Twitterdiabetessentiment analysissocial mediatype 1 diabetestype 2 diabetes

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Area of Science:

  • Computational Social Science
  • Health Informatics
  • Natural Language Processing

Background:

  • Social media content significantly influences individual perceptions and decision-making.
  • Understanding public sentiment towards diabetes is crucial for assessing the impact of online information on patients and their families.
  • The digital landscape, particularly platforms like Twitter, serves as a vital source for public health insights.

Purpose of the Study:

  • To analyze the sentiment expressed in Twitter messages concerning diabetes.
  • To investigate the relationship between specific diabetes types (T1D, T2D) and expressed sentiment.
  • To explore the influence of emojis and user follower count on sentiment polarity in diabetes-related tweets.

Main Methods:

  • Extraction of 67,421 tweets mentioning "diabetes," "t1d," or "t2d" using the Twitter API over one week.
  • Sentiment analysis performed using the SentiStrength tool on tweet text and user follower counts.
  • Statistical analysis to compare sentiment scores based on the presence of emojis and specific diabetes type mentions.

Main Results:

  • Tweets mentioning T2D without emojis were significantly more negative than those with emojis (-2.22 vs -1.48).
  • Tweets about T1D with emojis showed significantly more positive sentiment (1.71 vs 1.49) and less negative sentiment (-1.31 vs -1.50) compared to those without.
  • Higher follower counts were negatively associated with positive sentiment (r=-.023) and positively associated with negative sentiment (r=.016).

Conclusions:

  • Sentiment analysis of social media data offers valuable insights into public perception of diabetes.
  • The presence of emojis can mitigate negative sentiment and enhance positive sentiment in online diabetes discussions.
  • Understanding social media's impact on individuals with diabetes can inform public health strategies and interventions.