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10.1145/3099023.3099056acmconferencesArticle/Chapter ViewAbstractPublication PagesumapConference Proceedingsconference-collections
short-paper

A Detailed Analysis of the Impact of Tie Strength and Conflicts on Social Influence

Published: 09 July 2017 Publication History

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 affect 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 shifting, but the presence of conflict, instead, can lead to a negative influence, causing a drifting 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.

References

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Gediminas Adomavicius and Alexander Tuzhilin 2015. Context-aware recommender systems. Recommender systems handbook. Springer, 191--226.
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Francesco Barile, Judith Masthoff, and Silvia Rossi. 2017. The Adaptation of an Individual's Satisfaction to Group Context: the Role of Ties Strength and Conflicts. In Proceedings of the 2017 Conference on User Modeling Adaptation and Personalization. ACM.
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James C Cox, Daniel Friedman, and Steven Gjerstad. 2007. A tractable model of reciprocity and fairness. Games and Economic Behavior Vol. 59, 1 (2007), 17--45.
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Martin Dufwenberg, Paul Heidhues, Georg Kirchsteiger, Frank Riedel, and Joel Sobel. 2011. Other-Regarding Preferences in General Equilibrium. The Review of Economic Studies Vol. 78, 2 (2011), 613--639.
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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.
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Mark S Granovetter. 1973. The strength of weak ties. American journal of sociology Vol. 78, 6 (May 1973), 1360--1380.
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Judith Masthoff. 2015. Group recommender systems: Aggregation, satisfaction and group attributes. Recommender Systems Handbook. Springer, 743--776.
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Judith Masthoff and Albert Gatt 2006. In pursuit of satisfaction and the prevention of embarrassment: affective state in group recommender systems. User Modeling and User-Adapted Interaction Vol. 16, 3--4 (2006), 281--319.
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Silvia Rossi, Francesco Barile, Clemente Galdi, and Luca Russo 2017. Recommendation in museums: paths, sequences, and group satisfaction maximization. Multimedia Tools and Applications (2017).
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Silvia Rossi and Francesco Cervone 2016. Social Utilities and Personality Traits for Group Recommendation: A Pilot User Study Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,. INSTICC, ScitePress, 38--46.
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Cited By

View all
  • (2024)A Preliminary Study of the Impact of Personality on Satisfaction in Group ContextsAdjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization10.1145/3631700.3664893(319-328)Online publication date: 27-Jun-2024
  • (2022)Unpacking Intention and Behavior: Explaining Contact Tracing App Adoption and Hesitancy in the United StatesProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3501963(1-14)Online publication date: 29-Apr-2022
  • (2021)Integrating Collaboration and Leadership in Conversational Group Recommender SystemsACM Transactions on Information Systems10.1145/346275939:4(1-32)Online publication date: 17-Aug-2021
  • Show More Cited By

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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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New York, NY, United States

Publication History

Published: 09 July 2017

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Author Tags

  1. context-aware recommendation
  2. group recommendation
  3. opinion shift
  4. social influence

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Cited By

View all
  • (2024)A Preliminary Study of the Impact of Personality on Satisfaction in Group ContextsAdjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization10.1145/3631700.3664893(319-328)Online publication date: 27-Jun-2024
  • (2022)Unpacking Intention and Behavior: Explaining Contact Tracing App Adoption and Hesitancy in the United StatesProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3501963(1-14)Online publication date: 29-Apr-2022
  • (2021)Integrating Collaboration and Leadership in Conversational Group Recommender SystemsACM Transactions on Information Systems10.1145/346275939:4(1-32)Online publication date: 17-Aug-2021
  • (2019)Timing Information Propagation in Interactive NetworksScientific Reports10.1038/s41598-019-40801-59:1Online publication date: 14-Mar-2019

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