Conference Papers

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506

Browse

Search Results

Now showing 1 - 2 of 2
  • Item
    Exploring Depression Symptoms through Similarity Methods in Social Media Posts
    (CEUR-WS, 2023) Recharla, N.; Bolimera, P.; Gupta, Y.; Anand Kumar, M.
    Regardless of age, gender, or color, depression affects people all over the world. People feel increasingly at ease sharing their opinions on social networking sites practically every day in the present era of communication and technology. Reddit is a social networking site consisting of subreddits, or single-topic communities, created, maintained, and frequented by anonymous users. Users have the ability to post, comment on, and reply to posts within subreddits. Data for this suggested model is gathered from user posts on Reddit. Our approach involves ranking sentences from a collection of Reddit posts according to their relevance to a depression symptom for the 21 symptoms of depression from the BDI-II Questionnaire. © 2023 Copyright for this paper by its authors.
  • Item
    Depression Severity Detection from Social Media Posts
    (Springer Science and Business Media Deutschland GmbH, 2024) Recharla, N.; Bolimera, P.; Gupta, Y.; Anand Kumar, M.A.
    Regardless of age, gender, or color, mental health problems affect people all over the world. People feel increasingly at ease sharing their opinions on social networking sites (SNS) practically every day in the present era of communication and technology. Reddit is a social networking site that consists of subreddits, or single-topic communities, that are created, maintained, and frequented by anonymous users. The dataset used in the paper is, eRisk2021 dataset provided for task 3, which is used for depression severity measurement. It consists posts of Reddit users. In this paper, the approach involves finding user depression severity based on their Reddit history with the help of the BDI-II questionnaire, which is discussed. The paper provides three different approaches in finding the users depression severity from their social media data. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.