Prediction and detection of emotional tone in online social media mental disorder groups using regression and recurrent neural networks

Abstract

Online social media networks have become a significant platform for persons with mental illnesses to discuss their struggles and obtain emotional and informational assistance in recent years. One such platform is Reddit, where sub-groups called ‘subreddits’ exist, based on a variety of topics including mental illnesses such as anxiety or depression. We analyse the user’s interactions to calculate the mental health status by formulating and using a parameter called ‘emotional tone’ representing the user’s emotional state. VADER sentiment analysis and TextBlob are used to categorise emotional tone and find distribution of emotional polarity and subjectivity of comments. For final tone prediction, RNN and State-Of-The-Art word embedding techniques are used to develop a predictive model. The resultant model provides end-to-end categorization and prediction of emotional tone. We obtain results with respect to Weighted L1 Loss that deals with extreme responses. The MODEL transcends all the baselines by at least 12.1% and the final emotional status of the authors is positive.

Large Language Model–Based Responses to Patients’ In-Basket Messages

“… 50 , 51 , 52 , 53 The textblob package (version 0.17.1) facilitated sentiment analysis, a common method used to assess subjectivity (range 0 to 1, higher indicating more subjectivity) and polarity, or the overall positive/negative tone of a text (range −1 to 1, higher is more positive). 54 , 55 , 56 …”

Application of sentiment and word frequency analysis of physician review sites to evaluate refractive surgery care

“…VADER is a computational sentiment analysis tool that quantifies a writer's attitude, emotions, or judgements. 6 It considers punctuation and capitalization in addition to lexicon to determine the magnitude of emotions or sentiments and then assigns a score. VADER has been previously utilized in studies investigating the emotional tone of comments on online social media platforms such as Reddit, 6 Twitter, 7 , 8 and in healthcare on PRW to evaluate patient reviews.…”

“… 6 It considers punctuation and capitalization in addition to lexicon to determine the magnitude of emotions or sentiments and then assigns a score. VADER has been previously utilized in studies investigating the emotional tone of comments on online social media platforms such as Reddit, 6 Twitter, 7 , 8 and in healthcare on PRW to evaluate patient reviews. 3 , 4 , 9 Within ophthalmology, VADER analysis of PRWs, such as Healthgrades, has identified overall positive sentiment among patients, with specific concerns surrounding wait times and staff for pediatric ophthalmology and glaucoma providers.…”