Twitter User Modeling based on Indirect Explicit Relationships for Personalized Recommendations

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

doi:10.1007/978-3-030-28377-3_8

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 ISBN › Conference contribution with ISSN or ISBN › peer-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 language	English
Title of host publication	Computational Collective Intelligence - 11th International Conference, ICCCI 2019, Proceedings
Subtitle of host publication	11th International Conference, ICCCI 2019, Proceedings
Editors	Ngoc Thanh Nguyen, Richard Chbeir, Ernesto Exposito, Philippe Aniorté, Bogdan Trawinski, Ngoc Thanh Nguyen
Publisher	Springer International
Pages	93-105
Number of pages	13
ISBN (Print)	9783030283766
DOIs	https://doi.org/10.1007/978-3-030-28377-3_8
Publication status	Published - 9 Aug 2019
Event	11th International Conference on Computational Collective Intelligence, ICCCI 2019 - Hendaye , France Duration: 4 Sept 2019 → 6 Sept 2019 Conference number: 11 http://iccci.sigappfr.org

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11683 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	11th International Conference on Computational Collective Intelligence, ICCCI 2019
Abbreviated title	ICCCI
Country/Territory	France
City	Hendaye
Period	4/09/19 → 6/09/19
Internet address	http://iccci.sigappfr.org

Keywords

Recommender systems
User modeling
User profiling
Explicit relationships
Twitter

Access to Document

10.1007/978-3-030-28377-3_8

Twitter User Modeling based on Indirect Explicit Relationships for Personalized RecommendationsAccepted author manuscript, 364 KB

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 et al. / 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)).

@inproceedings{a7fd8215837948fe9712cd95e1a50034,

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{\textquoteright}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{\textquoteright} 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.",

keywords = "Recommender systems, User modeling, User profiling, Explicit relationships, Twitter",

author = "Abdullah Alshammari and Stelios Kapetanakis and Nikolaos Polatidis and Roger Evans and Gharbi Alshammari",

year = "2019",

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note = "11th International Conference on Computational Collective Intelligence, ICCCI 2019, ICCCI ; Conference date: 04-09-2019 Through 06-09-2019",

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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 et al.
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 ISBN › Conference contribution with ISSN or ISBN › peer-review

TY - GEN

T1 - Twitter User Modeling based on Indirect Explicit Relationships for Personalized Recommendations

AU - Alshammari, Abdullah

AU - Kapetanakis, Stelios

AU - Polatidis, Nikolaos

AU - Evans, Roger

AU - Alshammari, Gharbi

N1 - Conference code: 11

PY - 2019/8/9

Y1 - 2019/8/9

N2 - 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.

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.

KW - Recommender systems

KW - User modeling

KW - User profiling

KW - Explicit relationships

KW - Twitter

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U2 - 10.1007/978-3-030-28377-3_8

DO - 10.1007/978-3-030-28377-3_8

M3 - Conference contribution with ISSN or ISBN

SN - 9783030283766

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 93

EP - 105

BT - Computational Collective Intelligence - 11th International Conference, ICCCI 2019, Proceedings

A2 - Nguyen, Ngoc Thanh

A2 - Chbeir, Richard

A2 - Exposito, Ernesto

A2 - Aniorté, Philippe

A2 - Trawinski, Bogdan

A2 - Nguyen, Ngoc Thanh

PB - Springer International

T2 - 11th International Conference on Computational Collective Intelligence, ICCCI 2019

Y2 - 4 September 2019 through 6 September 2019

ER -

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)). doi: 10.1007/978-3-030-28377-3_8

Twitter User Modeling based on Indirect Explicit Relationships for Personalized Recommendations

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Nikolaos Polatidis

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Twitter User Modeling based on Indirect Explicit Relationships for Personalized Recommendations

Abstract

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Keywords

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Nikolaos Polatidis

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