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Social Network-Based Event Recommendation

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Book cover Computational Collective Intelligence (ICCCI 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10448))

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Abstract

The number of events generated on social networks has been growing quickly in recent years. It is difficult for users to find events that most suitably match their favorites. As a solution, the recommender system appears to solve this problem. However, event recommendation is significantly different from traditional recommendations, such as products and movies. Social events are created continuously, and only valid for a short time, so recommending a past event is meaningless. In this paper, we proposed a new even recommendation method based on social networks. First, the behavior of users be detected in order to build the user’s profile. Then the users’ relationship is extracted to measure the interaction strength between them. That is a fundamental factor affecting a decision of a user to attend events. In addition, the opinions about attended events are taken into account to evaluate the satisfaction of attendees by using deep learning method. Twitter is used as a case study for the method. The experiment shows that the method achieves promising results in comparison to other methods.

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Notes

  1. 1.

    https://www.meetup.com/about/.

  2. 2.

    https://www.eventbrite.com/.

  3. 3.

    https://about.twitter.com/company.

  4. 4.

    https://dev.twitter.com/rest/public.

  5. 5.

    http://tweepy.readthedocs.io/en/v3.5.0/.

  6. 6.

    texthttps://scrapy.org/.

  7. 7.

    https://www.eventbrite.com/.

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Acknowledgment

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (21C000151).

Author information

Authors and Affiliations

  1. Department of Computer Engineering, Yeungnam University, Gyeongsan, South Korea

    Dinh Tuyen Hoang & Dosam Hwang

  2. Quang Binh University, Quang Binh, Viet Nam

    Van Cuong Tran

Authors
  1. Dinh Tuyen Hoang
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  2. Van Cuong Tran
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  3. Dosam Hwang
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Corresponding author

Correspondence to Dosam Hwang .

Editor information

Editors and Affiliations

  1. Department of Information Systems, Faculty of Computer Science and Management , Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Department of Computer Science, University of Cyprus, Nicosia, Cyprus

    George A. Papadopoulos

  3. Department of Information Systems, Gdynia Maritime University, Gdynia, Poland

    Piotr Jędrzejowicz

  4. Department of Information Systems, Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

  5. Department of Information Systems, University of Münster, Münster, Germany

    Gottfried Vossen

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Hoang, D.T., Tran, V.C., Hwang, D. (2017). Social Network-Based Event Recommendation. In: Nguyen, N., Papadopoulos, G., Jędrzejowicz, P., Trawiński, B., Vossen, G. (eds) Computational Collective Intelligence. ICCCI 2017. Lecture Notes in Computer Science(), vol 10448. Springer, Cham. https://doi.org/10.1007/978-3-319-67074-4_18

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  • DOI: https://doi.org/10.1007/978-3-319-67074-4_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67073-7

  • Online ISBN: 978-3-319-67074-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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