Quantitative analysis of the relationship between expressing gratitude and forgiveness and user sentiment on social media

Abstract

Purpose The purpose of this study is to investigate how expressing gratitude and forgiveness on social media platforms relates to the overall sentiment of users, aiming to understand the impact of these expressions on social media interactions and individual well-being. Design/methodology/approach The hypothesis posits that users who frequently express gratitude or forgiveness will exhibit more positive sentiment in all posts during the observed period, compared to those who express these emotions less often. To test the hypothesis, sentiment analysis and statistical inference will be used. Additionally, topic modelling algorithms will be used to identify and assess the correlation between expressing gratitude and forgiveness and various topics. Findings This research paper explores the relationship between expressing gratitude and forgiveness in X (formerly known as Twitter) posts and the overall sentiment of user posts. The findings suggest correlations between expressing these emotions and the overall tone of social media content. The findings of this study can inform future research on how expressing gratitude and forgiveness can affect online sentiment and communication. Originality/value The authors have demonstrated that social media users who frequently express gratitude or forgiveness over an extended period of time exhibit a more positive sentiment compared to those who express these emotions less. Additionally, the authors observed that BERTopic modelling analysis performs better than latent dirichlet allocation and Top2Vec modelling analyses when analysing short messages from social media. This research, through the application of innovative techniques and the confirmation of previous theoretical findings, paves the way for further studies in the fields of positive psychology and machine learning.