Abstract
Performing observational studies based on social network content has recently gained attraction where the impact of various types of interruptions has been studied on users’ behavior. There has been recent work that have focused on how online social network behavior and activity can impact users’ offline behavior. In this paper, we study the inverse where we focus on whether users’ offline behavior captured through their check-ins at different venues on Foursquare can impact users’ online emotion expression as depicted in their tweets. We show that users’ offline activity can impact users’ online emotions; however, the type of activity determines the extent to which a user’s emotions will be impacted.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Ali, A.H.: The power of social media in developing nations: new tools for closing the global digital divide and beyond. Harv. Hum. Rts. J. 24, 185 (2011)
Althoff, T., Jindal, P., Leskovec, J.: Online actions with offline impact: how online social networks influence online and offline user behavior. In: Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, pp. 537–546. ACM (2017)
Brandtzæg, P.B.: Social networking sites: their users and social implications–a longitudinal study. J. Comput.-Mediated Commun. 17(4), 467–488 (2012)
Bucci, W., Freedman, N.: The language of depression. Bull. Menninger Clin. 45(4), 334 (1981)
Choudhury, M.D., Counts, S., Horvitz, E.: Predicting postpartum changes in emotion and behavior via social media. In: 2013 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2013, Paris, France, 27 April–2 May 2013, pp. 3267–3276 (2013)
Choudhury, M.D., Gamon, M., Counts, S., Horvitz, E.: Predicting depression via social media. In: Proceedings of the Seventh International Conference on Weblogs and Social Media, ICWSM 2013, Cambridge, Massachusetts, USA, 8–11 July 2013 (2013)
Cunha, T., Weber, I., Pappa, G.: A warm welcome matters!: the link between social feedback and weight loss in /r/loseit. In Proceedings of the 26th International Conference on World Wide Web Companion, pp. 1063–1072. International World Wide Web Conferences Steering Committee (2017)
De Choudhury, M., Kıcıman, E.: The language of social support in social media and its effect on suicidal ideation risk. In: Proceedings of the International AAAI Conference on Weblogs and Social Media. International AAAI Conference on Weblogs and Social Media, vol. 2017, p. 32. NIH Public Access (2017)
De Choudhury, M., Kiciman, E., Dredze, M., Coppersmith, G., Kumar, M.: Discovering shifts to suicidal ideation from mental health content in social media. In: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, pp. 2098–2110. ACM (2016)
De Choudhury, M., Sharma, S., Kiciman, E.: Characterizing dietary choices, nutrition, and language in food deserts via social media. In: Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, pp. 1157–1170. ACM (2016)
Dos Reis, V.L., Culotta, A.: Using matched samples to estimate the effects of exercise on mental health from twitter. In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, pp. 182–188 (2015)
Greaves, F., Ramirez-Cano, D., Millett, C., Darzi, A., Donaldson, L.: Harnessing the cloud of patient experience: using social media to detect poor quality healthcare. BMJ Qual. Saf. 22(3), 251–255 (2013)
Hu, R., Pu, P.: Enhancing collaborative filtering systems with personality information. In: Proceedings of the Fifth ACM Conference on Recommender Systems, pp. 197–204. ACM (2011)
Karumur, R.P., Nguyen, T.T., Konstan, J.A.: Exploring the value of personality in predicting rating behaviors: a study of category preferences on movielens. In: Proceedings of the 10th ACM Conference on Recommender Systems, pp. 139–142. ACM (2016)
Li, C., Lu, Y., Mei, Q., Wang, D., Pandey, S.: Click-through prediction for advertising in twitter timeline. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Sydney, NSW, Australia, 10–13 August 2015, pp. 1959–1968 (2015)
Liu, Y., Cao, X., Yu, Y.: Are you influenced by others when rating?: improve rating prediction by conformity modeling. In: Proceedings of the 10th ACM Conference on Recommender Systems, pp. 269–272. ACM (2016)
Oktay, H., Taylor, B.J., Jensen, D.D.: Causal discovery in social media using quasi-experimental designs. In: Proceedings of the First Workshop on Social Media Analytics, pp. 1–9. ACM (2010)
Oxman, T.E., Rosenberg, S.D., Tucker, G.J.: The language of paranoia. Am. J. Psychiatry 139(3), 275–282 (1982). https://doi.org/10.1176/ajp.139.3.275
Pennebaker, J.W., Mehl, M.R., Niederhoffer, K.G.: Psychological aspects of natural language use: our words, our selves. Ann. Rev. Psychol. 54(1), 547–577 (2003)
Roshchina, A., Cardiff, J., Rosso, P.: User profile construction in the twin personality-based recommender system (2011)
Sulistya, A., Sharma, A., Lo, D.: Spiteful, one-off, and kind: predicting customer feedback behavior on Twitter. In: Spiro, E., Ahn, Y.-Y. (eds.) SocInfo 2016. LNCS, vol. 10047, pp. 368–381. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-47874-6_26
Tausczik, Y.R., Pennebaker, J.W.: The psychological meaning of words: LIWC and computerized text analysis methods. J. Lang. Soc. Psychol. 29(1), 24–54 (2010)
Yang, S., Sklar, M.: Detecting trending venues using foursquare’s data. In: RecSys Posters (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Mirlohi Falavarjani, S.A., Hosseini, H., Bagheri, E. (2020). The Impact of Foursquare Checkins on Users’ Emotions on Twitter. In: Boratto, L., Faralli, S., Marras, M., Stilo, G. (eds) Bias and Social Aspects in Search and Recommendation. BIAS 2020. Communications in Computer and Information Science, vol 1245. Springer, Cham. https://doi.org/10.1007/978-3-030-52485-2_13
Download citation
DOI: https://doi.org/10.1007/978-3-030-52485-2_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-52484-5
Online ISBN: 978-3-030-52485-2
eBook Packages: Computer ScienceComputer Science (R0)