Anti-Depressants Twitter report for the week of September 4, 2022

Daily sentiment

Net daily sentiment ranged from -19.61 for on Sunday the 4th to 37.08 for on Tuesday the 6th.

The sentiment for each tweet is scored from -1 (most negative) to +1 (most positive) using VADER sentiment analysis. Net sentiment is calculated by summing the sentiment across all tweets for a given day and/or category, then normalizing the score by the number of tweets.

daily sentiment for tweets published between 2022-09-04 and 2022-09-10


Medical conditions from the MedDRA dictionary

Anxiety was the most frequently observed medical condition mentioned. Fall had the highest overall net sentiment of 32.1. Pain had the lowest net sentiment this week (-43.39).

medical condition count sentiment
Anxiety 62 -11.15
Pain 57 -43.39
Crying 18 -37.62
Numbness 17 -37.69
Fall 16 32.10
Sleepiness, Sleepy 14 -2.17
Coldness, Cold 13 -23.76
Insomnia 13 6.63
Sickness 13 -41.17
Forgetfulness 12 4.13

MedDra is a standardized medical terminology developed by the International Council for Harmonization Cross-referencing tweets against this list is a starting point for identifying medical conditions mentioned in tweets.


Cross-referencing the MedDRA dictionary by sentiment and topic

Positive tweets:

There were 101 tweets with an strong positive sentiment. The top 10 most frequent medical conditions mentioned within these tweets were (1) Anxiety, (2) Fall, (3) Pain, (4) Nightmare, Nightmares, (5) Headache, (6) Insomnia, (7) Migraine, (8) Weight gain, (9) ADHD, (10) Infection. Of these terms, Nightmare, Nightmares (n=5), Headache (n=4), Migraine (n=4), Weight gain (n=4), ADHD (n=3), Infection (n=3) were not in the top 10 most frequent terms across all tweets.

Meddra conditions associated with positive tweets published between 2022-09-04 and 2022-09-10

Negative tweets:

There were 158 tweets with an strong negative sentiment. The top 10 most frequent medical conditions mentioned within these tweets were (1) Pain, (2) Anxiety, (3) Crying, (4) Numbness, (5) Sickness, (6) Exhaustion, (7) Coldness, Cold, (8) Sleepiness, Sleepy, (9) Diabetic, Diabetes, (10) Forgetfulness. Of these terms, Exhaustion (n=6), Diabetic, Diabetes (n=3) were not in the top 10 most frequent terms across all tweets.

Meddra conditions associated with negative tweets published between 2022-09-04 and 2022-09-10


Word-level analysis

The 25 most important words within positive tweets (compared to negative and neutral) tweets are shown in the treemap below. The size of each box represents the weighted score of each word. The word “help” within the search for “Sertraline” had the highest overall weight. When the words are summed for each topic, Tryptophan had the highest overall weight.

words associated with positive tweets published between 2022-09-04 and 2022-09-10

The 25 most important words within negative tweets (compared to positive and neutral) tweets are shown in the treemap below. The word “veget” within the search for “Tryptophan” had the highest overall weight. When the words are summed for each topic, “Bupropion” had the highest overall weight within negative tweets.

words associated with negative tweets published between 2022-09-04 and 2022-09-10

This analysis of words evaluates the stemmed version of words using the Snowball algorithm. By stemming words, words with similar meaning, such as pain, painful & pained, are grouped together as simply “pain”.


References

Webpage created in R version 4.1.0 (2021-05-18) and R Studio (Version 1.4.1717) using the following packages: plotly, kableExtra, formattable, treemap, and wordpressr.

  • C. Sievert. Interactive Web-Based Data Visualization with R, plotly, and shiny. Chapman and Hall/CRC Florida, 2020.
  • Hao Zhu (2021). kableExtra: Construct Complex Table with ‘kable’ and Pipe Syntax. R package version 1.3.4.
  • Kun Ren and Kenton Russell (2021). formattable: Create ‘Formattable’ Data Structures. R package version 0.2.1.
  • Martijn Tennekes (2021). treemap: Treemap Visualization. R package version 2.4-3.
  • Simit Patel (2021). wordpressr: An API Wrapper for WordPress Site APIs. R package version 0.1.0.
  • Hutto, C.J. & Gilbert, E.E. (2014). VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text. Eighth International Conference on Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014.