SICLIRApr 11, 2014

Targeting HIV-related Medication Side Effects and Sentiment Using Twitter Data

arXiv:1404.3610v16 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the problem of understanding patient experiences with HIV medication side effects for the general public, but it is incremental as it applies existing methods to new data without novel methodological contributions.

The study tackled the problem of identifying HIV treatment side effects and user sentiment by analyzing Twitter data, resulting in an infographic summarizing side effects and a sentiment measure based on hand-rated tweets.

We present a descriptive analysis of Twitter data. Our study focuses on extracting the main side effects associated with HIV treatments. The crux of our work was the identification of personal tweets referring to HIV. We summarize our results in an infographic aimed at the general public. In addition, we present a measure of user sentiment based on hand-rated tweets.

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