TY - GEN
T1 - Cancer Through the Lens of Social Media
T2 - 7th International Conference on ICT for Sustainable Development , ICT4SD 2022
AU - Rao, Shreeya Sudhesh
AU - Vibha, null
AU - Shitij,
AU - Kamath, Giridhar B.
AU - Rao, Suchetha S.
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2023
Y1 - 2023
N2 - Cancer incidence and mortality is increasing globally. The people affected constantly remain in distress the family is under enormous financial and psychological pressure. Social media provides an excellent outlet to vent out all the feelings that develop in one’s mind, which could prove critical for one’s health and survival in cases such as cancer. Reddit is one such social platform with its subreddit dedicated to folks affected by cancer. Subreddit is estimated to be sentiment heavy. We aimed to examine these sentiments and categorize the kind of discussions within the cancer subreddit community, with the intent of categorizing the topic of discussion. Using Python, push shift application programming interface (API) was used nearly ten thousand posts were extracted. After proper data cleaning, we validated the authenticity of data extracted via visualization, then performed Latent Dirichlet Allocation (LDA) to categorize these posts using libraries to separate the posts based on semantics. The topics were categorized in to 3, most topics belonged to category 1 which included emotions, immediate response to diagnosis.
AB - Cancer incidence and mortality is increasing globally. The people affected constantly remain in distress the family is under enormous financial and psychological pressure. Social media provides an excellent outlet to vent out all the feelings that develop in one’s mind, which could prove critical for one’s health and survival in cases such as cancer. Reddit is one such social platform with its subreddit dedicated to folks affected by cancer. Subreddit is estimated to be sentiment heavy. We aimed to examine these sentiments and categorize the kind of discussions within the cancer subreddit community, with the intent of categorizing the topic of discussion. Using Python, push shift application programming interface (API) was used nearly ten thousand posts were extracted. After proper data cleaning, we validated the authenticity of data extracted via visualization, then performed Latent Dirichlet Allocation (LDA) to categorize these posts using libraries to separate the posts based on semantics. The topics were categorized in to 3, most topics belonged to category 1 which included emotions, immediate response to diagnosis.
UR - http://www.scopus.com/inward/record.url?scp=85142697439&partnerID=8YFLogxK
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U2 - 10.1007/978-981-19-5331-6_35
DO - 10.1007/978-981-19-5331-6_35
M3 - Conference contribution
AN - SCOPUS:85142697439
SN - 9789811953309
T3 - Lecture Notes in Networks and Systems
SP - 335
EP - 346
BT - ICT Infrastructure and Computing - Proceedings of ICT4SD 2022
A2 - Tuba, Milan
A2 - Akashe, Shyam
A2 - Joshi, Amit
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 29 July 2022 through 30 July 2022
ER -
