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Evaluating the importance of different communication types in romantic tie prediction on social media

  • Data Mining and Analytics
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Abstract

The purpose of this paper is to evaluate which communication types on social media are most indicative for romantic tie prediction. In contrast to analyzing communication as a composite measure, we take a disaggregated approach by modeling separate measures for commenting, liking and tagging focused on an alter’s status updates, photos, videos, check-ins, locations and links. To ensure that we have the best possible model we benchmark 8 classifiers using different data sampling techniques. The results indicate that we can predict romantic ties with very high accuracy. The top performing classification algorithm is adaboost with an accuracy of up to 97.89 %, an AUC of up to 97.56 %, a G-mean of up to 81.81 %, and a F-measure of up to 81.45 %. The top drivers of romantic ties were related to socio-demographic similarity and the frequency and recency of commenting, liking and tagging on photos, albums, videos and statuses. Previous research has largely focused on aggregate measures whereas this study focuses on disaggregate measures. Therefore, to the best of our knowledge, this study is the first to provide such an extensive analysis of romantic tie prediction on social media.

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Notes

  1. All time-related variables are expressed as number of days.

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Acknowledgments

The authors are thankful to the three anonymous reviewers whose comments have helped significantly improve an earlier version of this paper. The authors are also grateful to the Guest Editor of the Data Mining & Analytics Special Issue, Dr. Asil Oztekin, for his guidance and very timely management of this manuscript.

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Authors and Affiliations

  1. Department of Marketing, Ghent University, Tweekerkenstraat 2, 9000, Ghent, Belgium

    Matthias Bogaert & Dirk Van den Poel

  2. Department of Business Analytics and Statistics, The University of Tennessee, 249 Stokely Management Center, 916 Volunteer Blvd, Knoxville, TN, 37996, USA

    Michel Ballings

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  1. Matthias Bogaert
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Correspondence to Michel Ballings.

Appendix

Appendix

See Table 8.

Table 8 Median \(5\times 2\)cv accuracy, G-mean, F-measure and AUC per algorithm and per data sampling technique
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Bogaert, M., Ballings, M. & Van den Poel, D. Evaluating the importance of different communication types in romantic tie prediction on social media. Ann Oper Res 263, 501–527 (2018). https://doi.org/10.1007/s10479-016-2295-0

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