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Pokedem: an Automatic Social Media Management Application

Published: 27 August 2017 Publication History

Abstract

Typically, the task of managing the social media presence of a company or a public person is the job of a dedicated social media account manager. While many attempts have been made in recent years to provide more automation to account managers, complete workflow automation has still to be achieved. Pokedem is a social media management application that aims at filling this gap, recommending actions that could be performed by the account manager to increase the popularity of a Twitter account and the engagement of its audience. By casting the problem in the setting of recommendation systems, Pokedem is able to provide account managers with a complete tool for automating their daily activities.

References

[1]
Oana Barbu. 2014. Advertising, Microtargeting and Social Media. Procedia - Social and Behavioral Sciences 163 (2014), 44--49.
[2]
Pankaj Gupta, Ashish Goel, Jimmy Lin, Aneesh Sharma, Dong Wang, and Reza Zadeh. 2013. WTF: The Who to Follow Service at Twitter. In WWW. 505--514.
[3]
Su Mon Kywe, Ee-Peng Lim, and Feida Zhu. 2012. A Survey of Recommender Systems in Twitter. In Proc. of Int. Conf. on Social Informatics (SocInfo). 420--433.
[4]
Pasquale Lops, Marco de Gemmis, and Giovanni Semeraro. 2011. Content-based Recommender Systems: State of the Art and Trends. 73--105.
[5]
Yaroslav Nechaev, Francesco Corcoglioniti, and Claudio Giuliano. 2017. Linking Knowledge Bases to Social Media Profiles. In Proc. of ACM SAC. 145--150.
[6]
Jordi Paniagua and Juan Sapena. 2014. Business performance and social media: Love or hate? Business Horizons 57, 6 (2014), 719--728.

Cited By

View all
  • (2018)An application to manage widespread social media accounts with one smart touch2018 Fifth International Conference on Software Defined Systems (SDS)10.1109/SDS.2018.8370440(176-181)Online publication date: Apr-2018
  • (2018)SocialLink: exploiting graph embeddings to link DBpedia entities to Twitter profilesProgress in Artificial Intelligence10.1007/s13748-018-0160-x7:4(251-272)Online publication date: 8-Sep-2018
  • (2018)Twitter User Recommendation for Gaining FollowersAI*IA 2018 – Advances in Artificial Intelligence10.1007/978-3-030-03840-3_40(539-552)Online publication date: 9-Nov-2018

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cover image ACM Conferences
RecSys '17: Proceedings of the Eleventh ACM Conference on Recommender Systems
August 2017
466 pages
ISBN:9781450346528
DOI:10.1145/3109859
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 August 2017

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Author Tags

  1. machine learning
  2. recommender system
  3. social media management

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  • Demonstration

Funding Sources

  • European Institute of Innovation and Technology

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RecSys '17
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Acceptance Rates

RecSys '17 Paper Acceptance Rate 26 of 125 submissions, 21%;
Overall Acceptance Rate 254 of 1,295 submissions, 20%

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Cited By

View all
  • (2018)An application to manage widespread social media accounts with one smart touch2018 Fifth International Conference on Software Defined Systems (SDS)10.1109/SDS.2018.8370440(176-181)Online publication date: Apr-2018
  • (2018)SocialLink: exploiting graph embeddings to link DBpedia entities to Twitter profilesProgress in Artificial Intelligence10.1007/s13748-018-0160-x7:4(251-272)Online publication date: 8-Sep-2018
  • (2018)Twitter User Recommendation for Gaining FollowersAI*IA 2018 – Advances in Artificial Intelligence10.1007/978-3-030-03840-3_40(539-552)Online publication date: 9-Nov-2018

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