A detailed analysis of the impact of tie strength and conflicts on social influence

Francesco Barile, Judith Masthoff, Silvia Rossi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Group Recommendation Systems (GRS) are personalization systems that provide recommendations to groups of people considering the initial preferences of each group's member, with the aim to maximize the satisfaction of the whole group. Since recent psychological studies evidence that people's satisfaction is influenced by the satisfaction of other people with whom they perform an activity, it is important to consider human aspects and social characteristics that a.ect the changes in individual's satisfactions in the recommendations generation process. In this work, we start an experimental analysis on how ties' strength and possible conflicts in a relationship can influence the individual's satisfactions, with the aim to derive a model that can be used to adapt individual utilities to the "Group Context" before aggregating them into the group's ones. Our hypothesis is that there is a direct correlation between tie strength and positive shi.ing, but the presence of con.ict, instead, can lead to a negative influence, causing a dri.ing further apart between people's satisfactions. Results confirm these hypotheses, but also suggest that these two factors are not enough to define a general model and that other factors must be considered.

Original languageEnglish
Title of host publicationUMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization
PublisherAssociation for Computing Machinery, Inc
Pages227-230
Number of pages4
ISBN (Electronic)9781450350679
DOIs
Publication statusPublished - 9 Jul 2017
Event25th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2017 - Bratislava, Slovakia
Duration: 9 Jul 201712 Jul 2017

Conference

Conference25th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2017
CountrySlovakia
CityBratislava
Period9/07/1712/07/17

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Recommender systems

Keywords

  • Context-aware recommendation
  • Group recommendation
  • Opinion shift
  • Social influuence

ASJC Scopus subject areas

  • Software

Cite this

Barile, F., Masthoff, J., & Rossi, S. (2017). A detailed analysis of the impact of tie strength and conflicts on social influence. In UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization (pp. 227-230). Association for Computing Machinery, Inc. https://doi.org/10.1145/3099023.3099056

A detailed analysis of the impact of tie strength and conflicts on social influence. / Barile, Francesco; Masthoff, Judith; Rossi, Silvia.

UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, Inc, 2017. p. 227-230.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Barile, F, Masthoff, J & Rossi, S 2017, A detailed analysis of the impact of tie strength and conflicts on social influence. in UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, Inc, pp. 227-230, 25th ACM International Conference on User Modeling, Adaptation, and Personalization, UMAP 2017, Bratislava, Slovakia, 9/07/17. https://doi.org/10.1145/3099023.3099056
Barile F, Masthoff J, Rossi S. A detailed analysis of the impact of tie strength and conflicts on social influence. In UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, Inc. 2017. p. 227-230 https://doi.org/10.1145/3099023.3099056
Barile, Francesco ; Masthoff, Judith ; Rossi, Silvia. / A detailed analysis of the impact of tie strength and conflicts on social influence. UMAP 2017 - Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, Inc, 2017. pp. 227-230
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