Abstract
We can use data from social media to examine and uncover links between positive and negative emotions. The findings of this article can be applied to a variety of subjects, including psychology and sociology. The goal was to provide insight into various observations made during our analysis. For this, we used Reddit comments as a reference point and data analytics to obtain various results. Our contributions to this paper are to grasp the concept of emotions and appropriately evaluate the data and analyzing Reddit comments and attempting to answer questions regarding the data acquired and discussing potential improvements to our analysis for future works in the field. We selected Reddit since it includes roughly 50 default subreddit themes that are accessible on the home page, including news, gaming, movies, music, and many others. Furthermore, redditors have the option of creating their own subreddit. Moreover, Reddit is one of the world's most prominent social networking websites. This makes it appropriate for our needs because it has a large number of user comments, which we can simply retrieve using the easy to use Pushshift API. The acquired comments data was then cleaned and analyzed using R in Rstudio and results were generated. Based on the results, conclusions were generated like correlations and mean values.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Narwekar, A.: Affective analysis of text in tweets. University of Illinois (2018). https://www.ideals.illinois.edu/handle/2142/101090
Griffiths, P.E.: III. Basic emotions, complex emotions, machiavellian emotions. Royal Inst. Philos. Suppl. 52, pp 39–67 (2003)
Scherer, K.R.: What are emotions? And how can they be measured? Soc. Sci. Inf. 44(4), 695–729 (2005)
Madhala, P.: Detecting consumer emotions on social networking websites. Tampere University (2019). https://www.researchgate.net/publication/336891523_Detecting_Consumer_Emotions_On_Social_Networking_Websites
Kusen, E., Cascavilla, G., Figl, K., Conti, M., Strembeck, M.: Identifying emotions in social media: comparison of word-emotion lexicons. In: IEEE International Conference on Future Internet of Things and Cloud Workshops, Czech Republic (2017)
Widen, G., Lindstrom, J., Brannback, M., Huvila, I, Nystrom, A.G.: Mixed emotions in active social media use—fun and convenient or shameful and embarrassing? iConference (2015)
Botzer, N., Gu, S., Weninger, T.: Analysis of moral judgement on reddit. Soc. Inf. Netw. (2021)
Suler, J.: The online disinhibition effect. Cyber Psychol. Behav. 7(3), (2004)
Schober, P., Boer, C., Schwarte, L.A.: Correlation coefficients: appropriate use and interpretation. Anesth. Analg. 126(5), 1763–1768 (2018)
Adeyemi, O.: Measures of association for research in educational planning and administration. Res. J. Math. Stat. 3(3), 82–90 (2011)
Mohammad, S.M.: Sentiment analysis: automatically detecting valence, emotions and other affectual states from text. Comput. Lang. (2021)
Al-Amin, M., Islam, M.S., Uzzal, SD: A comprehensive study on sentiment of bengali text. In: International Conference on Electrical, Computer and Communication Engineering, IEEE, Bangladesh, pp 267–272 (2017)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Palit, S., Pradhan, C., Elngar, A.A. (2023). A Descriptive Analysis of Reddit Comments Using Data Analytics Approach. In: Bhateja, V., Yang, XS., Lin, J.CW., Das, R. (eds) Evolution in Computational Intelligence. FICTA 2022. Smart Innovation, Systems and Technologies, vol 326. Springer, Singapore. https://doi.org/10.1007/978-981-19-7513-4_16
Download citation
DOI: https://doi.org/10.1007/978-981-19-7513-4_16
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-19-7512-7
Online ISBN: 978-981-19-7513-4
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)