TY - GEN
T1 - Linguistic and Contextual Analysis of SNS Posts for Approval Desire
AU - Murata, Erina
AU - Tago, Kiichi
AU - Jin, Qun
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - In recent years, SNS has become a service that everyone uses. In this study, we analyze Twitter, one of the most popular SNSs, which allows users to post their daily events and feelings within 140 characters and is used by people all over the world. In this study, we investigate the relationship between SNS posts and latent approval needs. The linguistic features of tweets and their contextual features are analyzed using information such as the frequency of posts and the number of characters in tweets, and the degree of desire for approval is defined and quantified based on the results of the analysis of tweets. The experiment results show that the agreement between the naïve Bayes classifier and human ratings was about 60%. It is found that users with a high percentage of posts for approval desire tend to post less frequently and with a higher average number of characters. This indicates that it may be because these users post for approval desire when it is important or when they really want to say something.
AB - In recent years, SNS has become a service that everyone uses. In this study, we analyze Twitter, one of the most popular SNSs, which allows users to post their daily events and feelings within 140 characters and is used by people all over the world. In this study, we investigate the relationship between SNS posts and latent approval needs. The linguistic features of tweets and their contextual features are analyzed using information such as the frequency of posts and the number of characters in tweets, and the degree of desire for approval is defined and quantified based on the results of the analysis of tweets. The experiment results show that the agreement between the naïve Bayes classifier and human ratings was about 60%. It is found that users with a high percentage of posts for approval desire tend to post less frequently and with a higher average number of characters. This indicates that it may be because these users post for approval desire when it is important or when they really want to say something.
KW - Approval desire
KW - Internet psychology
KW - Naïve Bayes
KW - SNS
KW - Text mining
KW - Twitter
UR - http://www.scopus.com/inward/record.url?scp=85133031523&partnerID=8YFLogxK
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U2 - 10.1007/978-3-031-05061-9_24
DO - 10.1007/978-3-031-05061-9_24
M3 - Conference contribution
AN - SCOPUS:85133031523
SN - 9783031050602
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 332
EP - 344
BT - Social Computing and Social Media
A2 - Meiselwitz, Gabriele
PB - Springer Science and Business Media Deutschland GmbH
T2 - 14th International Conference on Social Computing and Social Media, SCSM 2022 Held as Part of the 24th HCI International Conference, HCII 2022
Y2 - 26 June 2022 through 1 July 2022
ER -