Abstract
The various mobile social APPs greatly enrich the way people communicate with each other. It has been argued that the use of mobile social APPs may influence user mobile phone call behaviour, as more and more people are used to using mobile social APPs for voice or video calls. Although mobile social APPs has penetrated into every aspect of our daily lives, so far there is no convincing research showing how the mobile social APPs influence the use of traditional mobile phone calls. Based on the potential outcomes model, we use the potential outcomes model to study the causal effects of the frequent use of mobile social APPs on mobile phone calls. The propensity score matching method is performed for bias adjustment. Moreover, the sensitivity analysis is conducted to test whether the results remained robust in the presence of hidden biases. The results suggest statistically significant positive effects of frequent use of Wechat on traditional mobile phone calls. But for QQ, we found that frequent use of QQ reduces mobile phone calls. The conclusion provides a new theoretical feature for business package recommendation, namely, the frequency of mobile social APPs. For WeChat users who use WeChat frequently, they are more inclined to provide business package containing high call duration, and for QQ users who use QQ frequently, they are more inclined to provide business package containing low call duration, which further enriches the method of business package recommendation.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Althoff, T., Jindal, P., Leskovec, J.: Online actions with offline impact: how online social networks influence online and offline user behavior (2016)
Atzmueller, M.: Analyzing and grounding social interaction in online and offline networks. In: Calders, T., Esposito, F., Hüllermeier, E., Meo, R. (eds.) ECML PKDD 2014. LNCS (LNAI), vol. 8726, pp. 485–488. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-44845-8_41
Austin, P.C.: An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav. Res. 46(3), 399–424 (2011)
Burke, M., Kraut, R.E.: The relationship between facebook use and well-being depends on communication type and tie strength: Facebook and well-being. J. Comput.-Mediat. Commun. 21(4), 265–281 (2016)
Dunbar, R.I.: Do online social media cut through the constraints that limit the size of offline social networks? R. Soc. Open Sci. 3(1), 150292 (2016)
Dunbar, R.I.M., Arnaboldi, V., Conti, M., Passarella, A.: The structure of online social networks mirrors those in the offline world. Soc. Netw. 43, 39–47 (2015)
Gwenn Schurgin, O., Kathleen, C.P.: The impact of social media on children, adolescents, and families. Pediatrics 127(4), 800 (2011)
Hsu, J.Y., Small, D.S., Rosenbaum, P.R.: Effect modification and design sensitivity in observational studies. J. Am. Stat. Assoc. 108(501), 135–148 (2013)
Laranjo, L., et al.: The influence of social networking sites on health behavior change: a systematic review and meta-analysis. J. Am. Med. Inform. Assoc. 22(1), 243–256 (2014)
Meng, J.: Your health buddies matter: preferential selection and social influence on weight management in an online health social network. Health Commun. 31(12), 1 (2016)
Oh, H.J., Ozkaya, E., Larose, R.: How does online social networking enhance life satisfaction? The relationships among online supportive interaction, affect, perceived social support, sense of community, and life satisfaction. Comput. Hum. Behav. 30(1), 69–78 (2014)
Reich, S.M., Subrahmanyam, K., Espinoza, G.: Friending, iming, and hanging out face-to-face: Overlap in adolescents’ online and offline social networks. Dev. Psychol. 48(2), 356 (2012)
Rosenbaum, P.R.: Design of Observational Studies (2010)
Sabatini, F., Sarracino, F.: Online social networks and trust. Soc. Indicat. Res. 2, 1–32 (2015)
Shi, J., Salmon, C.T.: Identifying opinion leaders to promote organ donation on social media: network study. J. Med. Internet Res. 20(1), e7 (2018)
Song, H., et al.: Does facebook make you lonely?: A meta analysis. Comput. Hum. Behav. 36(36), 446–452 (2014)
Utz, S.: The function of self-disclosure on social network sites: not only intimate, but also positive and entertaining self-disclosures increase the feeling of connection. Comput. Hum. Behav. 45, 1–10 (2015)
Westreich, D., Lessler, J., Funk, M.J.: Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regression. J. Clin. Epidemiol. 63(8), 826–833 (2010)
Yadav, M., Joshi, Y., Rahman, Z.: Mobile social media: the new hybrid element of digital marketing communications. Proc. - Soc. Behav. Sci. 189, 335–343 (2015)
Yang, S., Wang, B., Lu, Y.: Exploring the dual outcomes of mobile social networking service enjoyment: the roles of social self-efficacy and habit. Comput. Hum. Behav. 64, 486–496 (2016)
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Jiang, H. et al. (2019). Do Top Social Apps Effect Voice Call? Evidence from Propensity Score Matching Methods. In: Qiu, M. (eds) Smart Computing and Communication. SmartCom 2019. Lecture Notes in Computer Science(), vol 11910. Springer, Cham. https://doi.org/10.1007/978-3-030-34139-8_14
Download citation
DOI: https://doi.org/10.1007/978-3-030-34139-8_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-34138-1
Online ISBN: 978-3-030-34139-8
eBook Packages: Computer ScienceComputer Science (R0)