Twitter User Modeling based on Indirect Explicit Relationships for Personalized Recommendations

Abdullah Alshammari, Stelios Kapetanakis, Nikolaos Polatidis, Roger Evans, Gharbi Alshammari

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBNResearchpeer-review

Abstract

Information overload has increased due to social network website use in recent times. Social media has increased the popularity of websites such as Twitter. It is believed that a rich environment is provided through Twitter whereby information sharing will be able to aid in recommender system research. This paper will focus upon Twitter user modeling through the utilization of indirect explicit relationships that exist amongst users. The further aim of this paper is to ensure that personal profiles are built via the use of information that will be sourced from Twitter so as to provide recommendations that are more accurate. The proposed method adopts Twitter user’s indirect explicit relationships in order to get information which is vital in the process of building personal user profiles. The proposed method has been validated through the implementation of an offline evaluation using real data. Proposed user profiles’ performances have been compared with each other and against the baseline profile. The performance of this has been validated using real data and is both practical and effective.

Original languageEnglish
Title of host publicationComputational Collective Intelligence - 11th International Conference, ICCCI 2019, Proceedings
Subtitle of host publication11th International Conference, ICCCI 2019, Proceedings
EditorsNgoc Thanh Nguyen, Richard Chbeir, Ernesto Exposito, Philippe Aniorté, Bogdan Trawinski, Ngoc Thanh Nguyen
PublisherSpringer International
Pages93-105
Number of pages13
ISBN (Print)9783030283766
DOIs
Publication statusPublished - 9 Aug 2019
Event11th International Conference on Computational Collective Intelligence, ICCCI 2019 - Hendaye , France
Duration: 4 Sep 20196 Sep 2019
Conference number: 11
http://iccci.sigappfr.org

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11683 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Computational Collective Intelligence, ICCCI 2019
Abbreviated titleICCCI
CountryFrance
CityHendaye
Period4/09/196/09/19
Internet address

Fingerprint

Personalized Recommendation
User Modeling
Websites
User Profile
Recommender systems
Social Media
Recommender Systems
Information Sharing
Overload
Social Networks
Recommendations
Baseline
Evaluation
Relationships
Profile

Keywords

  • Recommender systems
  • User modeling
  • User profiling
  • Explicit relationships
  • Twitter

Cite this

Alshammari, A., Kapetanakis, S., Polatidis, N., Evans, R., & Alshammari, G. (2019). Twitter User Modeling based on Indirect Explicit Relationships for Personalized Recommendations. In N. T. Nguyen, R. Chbeir, E. Exposito, P. Aniorté, B. Trawinski, & N. T. Nguyen (Eds.), Computational Collective Intelligence - 11th International Conference, ICCCI 2019, Proceedings: 11th International Conference, ICCCI 2019, Proceedings (pp. 93-105). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11683 LNAI). Springer International. https://doi.org/10.1007/978-3-030-28377-3_8
Alshammari, Abdullah ; Kapetanakis, Stelios ; Polatidis, Nikolaos ; Evans, Roger ; Alshammari, Gharbi. / Twitter User Modeling based on Indirect Explicit Relationships for Personalized Recommendations. Computational Collective Intelligence - 11th International Conference, ICCCI 2019, Proceedings: 11th International Conference, ICCCI 2019, Proceedings. editor / Ngoc Thanh Nguyen ; Richard Chbeir ; Ernesto Exposito ; Philippe Aniorté ; Bogdan Trawinski ; Ngoc Thanh Nguyen. Springer International, 2019. pp. 93-105 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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title = "Twitter User Modeling based on Indirect Explicit Relationships for Personalized Recommendations",
abstract = "Information overload has increased due to social network website use in recent times. Social media has increased the popularity of websites such as Twitter. It is believed that a rich environment is provided through Twitter whereby information sharing will be able to aid in recommender system research. This paper will focus upon Twitter user modeling through the utilization of indirect explicit relationships that exist amongst users. The further aim of this paper is to ensure that personal profiles are built via the use of information that will be sourced from Twitter so as to provide recommendations that are more accurate. The proposed method adopts Twitter user’s indirect explicit relationships in order to get information which is vital in the process of building personal user profiles. The proposed method has been validated through the implementation of an offline evaluation using real data. Proposed user profiles’ performances have been compared with each other and against the baseline profile. The performance of this has been validated using real data and is both practical and effective.",
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Alshammari, A, Kapetanakis, S, Polatidis, N, Evans, R & Alshammari, G 2019, Twitter User Modeling based on Indirect Explicit Relationships for Personalized Recommendations. in NT Nguyen, R Chbeir, E Exposito, P Aniorté, B Trawinski & NT Nguyen (eds), Computational Collective Intelligence - 11th International Conference, ICCCI 2019, Proceedings: 11th International Conference, ICCCI 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11683 LNAI, Springer International, pp. 93-105, 11th International Conference on Computational Collective Intelligence, ICCCI 2019, Hendaye , France, 4/09/19. https://doi.org/10.1007/978-3-030-28377-3_8

Twitter User Modeling based on Indirect Explicit Relationships for Personalized Recommendations. / Alshammari, Abdullah; Kapetanakis, Stelios; Polatidis, Nikolaos; Evans, Roger; Alshammari, Gharbi.

Computational Collective Intelligence - 11th International Conference, ICCCI 2019, Proceedings: 11th International Conference, ICCCI 2019, Proceedings. ed. / Ngoc Thanh Nguyen; Richard Chbeir; Ernesto Exposito; Philippe Aniorté; Bogdan Trawinski; Ngoc Thanh Nguyen. Springer International, 2019. p. 93-105 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11683 LNAI).

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBNResearchpeer-review

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AB - Information overload has increased due to social network website use in recent times. Social media has increased the popularity of websites such as Twitter. It is believed that a rich environment is provided through Twitter whereby information sharing will be able to aid in recommender system research. This paper will focus upon Twitter user modeling through the utilization of indirect explicit relationships that exist amongst users. The further aim of this paper is to ensure that personal profiles are built via the use of information that will be sourced from Twitter so as to provide recommendations that are more accurate. The proposed method adopts Twitter user’s indirect explicit relationships in order to get information which is vital in the process of building personal user profiles. The proposed method has been validated through the implementation of an offline evaluation using real data. Proposed user profiles’ performances have been compared with each other and against the baseline profile. The performance of this has been validated using real data and is both practical and effective.

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Alshammari A, Kapetanakis S, Polatidis N, Evans R, Alshammari G. Twitter User Modeling based on Indirect Explicit Relationships for Personalized Recommendations. In Nguyen NT, Chbeir R, Exposito E, Aniorté P, Trawinski B, Nguyen NT, editors, Computational Collective Intelligence - 11th International Conference, ICCCI 2019, Proceedings: 11th International Conference, ICCCI 2019, Proceedings. Springer International. 2019. p. 93-105. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-28377-3_8