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User's Social Media Profile as Predictor of Empathy

Published: 09 July 2017 Publication History

Abstract

The use of social media, like Facebook, Twitter and LinkedIn, is nowadays very common and quite for sure each one of us has at least a digital profile on them. The information left of these platforms such as likes, posts, tweets and photos are very informative and can be used for deducting our preferences, tendencies and behaviors. The analysis of the social media footprints has become a relevant research topic in the last decade and many works have demonstrated how to extract some traits of the user's affective sphere. In this paper, we focus on the prediction of empathic tendencies of a subject as an index of the influence of emotions during decisional processes. This value can be included in the user profile and can be relevant in some scenarios, such as music and movie recommender systems, where the emotional component is strongly delineated. We propose an approach of empathy level prediction based on a linear regression algorithm over Facebook profiles. We use a word2vec representation of the textual contents of the user's time-line posts, a LDA and SVD vector representation of the user's likes and other general descriptive data. The evaluation performed has demonstrated the validity of the approach for predicting the empathy tendency and the results have showed some relevant correlations with some specific groups of user's descriptive features.

References

[1]
Cecilie Schou Andreassen, Torbjørn Torsheim, Geir Scott Brunborg, and Ståle Pallesen. 2012. Development of a Facebook addiction scale. Psychological reports 110, 2 (2012), 501--517.
[2]
Simon Baron-Cohen and Sally Wheelwright. 2004. The empathy quotient: an investigation of adults with Asperger syndrome or high functioning autism, and normal sex differences. Journal of autism and developmental disorders 34, 2 (2004), 163--175.
[3]
Christian Becker-Asano, Helmut Prendinger, Mitsuro Ishizuka, and Ipke Wachsmuth. 2005. Empathy for Max (Preliminary project report). In Proceedings of the International Conference on Active Media Technology (AMT 2005) .
[4]
David M. Blei, Andrew Y. Ng, and Michael I. Jordan. 2003. Latent dirichlet allocation. Journal of machine Learning research 3, Jan (2003), 993--1022.
[5]
Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen, Koray Kavukcuoglu, and Pavel Kuksa. 2011. Natural language processing (almost) from scratch. Journal of Machine Learning Research 12, Aug (2011), 2493--2537.
[6]
Teresa Correa, Amber Willard Hinsley, and Homero Gil De Zuniga. 2010. Who interacts on the Web?: The intersection of users' personality and social media use. Computers in Human Behavior 26, 2 (2010), 247--253.
[7]
Mark H. Davis. 1980. A multidimensional approach to individual differences in empathy. (1980).
[8]
Rosalind F. Dymond. 1949. A scale for the measurement of empathic ability. Journal of consulting psychology 13, 2 (1949), 127.
[9]
Allen L. Edwards. 1976. An introduction to linear regression and correlation. (1976).
[10]
Eric Gilbert and Karrie Karahalios. 2009. Predicting tie strength with social media. In Proceedings of the SIGCHI conference on human factors in computing systems. ACM, 211--220.
[11]
Jennifer Golbeck, Cristina Robles, and Karen Turner. 2011. Predicting personality with social media. In CHI'11 extended abstracts on human factors in computing systems. ACM, 253--262.
[12]
Lewis R. Goldberg, John A. Johnson, Herbert W. Eber, Robert Hogan, Michael C. Ashton, C. Robert Cloninger, and Harrison G. Gough. 2006. The international personality item pool and the future of public-domain personality measures. Journal of Research in personality 40, 1 (2006), 84--96.
[13]
Yoav Goldberg. 2015. A Primer on Neural Network Models for Natural Language Processing. CoRR abs/1510.00726 (2015). http://arxiv.org/abs/1510.00726
[14]
Mark A. Hall and Lloyd A. Smith. 1998. Practical feature subset selection for machine learning. (1998).
[15]
Zellig Harris. 1954. Distributional structure. Word 10, 23 (1954), 146--162.
[16]
Robert Hogan. 1969. Development of an empathy scale. Journal of consulting and clinical psychology 33, 3 (1969), 307.
[17]
Lauren A. Jelenchick, Jens C. Eickhoff, and Megan A. Moreno. 2013. "Facebook depression?" Social networking site use and depression in older adolescents. Journal of Adolescent Health 52, 1 (2013), 128--130.
[18]
Michal Kosinski, Sandra C. Matz, Samuel D. Gosling, Vesselin Popov, and David Stillwell. 2015. Facebook as a research tool for the social sciences: Opportunities, challenges, ethical considerations, and practical guidelines. American Psychologist 70, 6 (2015), 543.
[19]
Thomas K. Landauer. 2006. Latent semantic analysis. Wiley Online Library.
[20]
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781 (2013).
[21]
John Neter, Michael H. Kutner, Christopher J. Nachtsheim, and William Wasserman. 1996. Applied linear statistical models. Vol. 4. Irwin Chicago.
[22]
Alvaro Ortigosa, Rosa M Carro, and José Ignacio Quroga. 2014. Predicting user personality by mining social interactions in Facebook. Journal of computer and System Sciences 80, 1 (2014), 57--71.
[23]
John Platt. 1998. Sequential minimal optimization: A fast algorithm for training support vector machines. (1998).
[24]
Helmut Prendinger and Mitsuru Ishizuka. 2005. The empathic companion: A character-based interface that addresses users'affective states. Applied Artificial Intelligence 19, 3--4 (2005), 267--285.
[25]
Marcin Skowron, Marko Tkalčič, Bruce Ferwerda, and Markus Schedl. 2016. Fusing social media cues: personality prediction from twitter and instagram. In Proceedings of the 25th international conference companion on world wide web . International World Wide Web Conferences Steering Committee, 107--108.
[26]
Dolf Zillmann. 1991. Empathy: Affect from bearing witness to the emotions of others. Responding to the screen: Reception and reaction processes (1991), 135--167.

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  • (2023)A Probabilistic Mapping Approach to Assess the Employee Behavior Profile2023 IEEE 25th Conference on Business Informatics (CBI)10.1109/CBI58679.2023.10187416(1-8)Online publication date: 21-Jun-2023

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cover image ACM Conferences
UMAP '17: Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization
July 2017
456 pages
ISBN:9781450350679
DOI:10.1145/3099023
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 09 July 2017

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Author Tags

  1. empathy
  2. machine learning
  3. social medium footprint

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  • H2020 Marie SkBodowska-Curie Actions

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UMAP '17
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Overall Acceptance Rate 162 of 633 submissions, 26%

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  • (2023)A Probabilistic Mapping Approach to Assess the Employee Behavior Profile2023 IEEE 25th Conference on Business Informatics (CBI)10.1109/CBI58679.2023.10187416(1-8)Online publication date: 21-Jun-2023

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