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Increasing Activity in Enterprise Online Communities Using Content Recommendation

Published: 13 August 2016 Publication History

Abstract

Although online communities have become popular both on the web and within enterprises, many of them often experience low levels of activity and engagement from their members. Previous studies identified the important role of community leaders in maintaining the health and vitality of their communities. One of their key means for doing so is by contributing relevant content to the community. In this paper, we study the effects of recommending social media content on enterprise community leaders. We conducted a large-scale user survey with four recommendation rounds, in which community leaders indicated their willingness to share social media items with their communities. They also had the option to instantly share these items. Recommendations were generated based on seven types of community interest profiles that were member-based, content-based, or hybrid. Our results attest that providing content recommendations to leaders can help uplift activity within their communities.

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Published In

cover image ACM Transactions on Computer-Human Interaction
ACM Transactions on Computer-Human Interaction  Volume 23, Issue 4
September 2016
199 pages
ISSN:1073-0516
EISSN:1557-7325
DOI:10.1145/2983309
Issue’s Table of Contents
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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Publication History

Published: 13 August 2016
Accepted: 01 March 2016
Revised: 01 October 2015
Received: 01 January 2015
Published in TOCHI Volume 23, Issue 4

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Author Tags

  1. Enterprise
  2. engagement
  3. group recommendation
  4. online communities
  5. social business
  6. social recommender systems

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Cited By

View all
  • (2025)An introduction to collaborative filtering through the lens of the Netflix PrizeKnowledge and Information Systems10.1007/s10115-024-02315-zOnline publication date: 10-Jan-2025
  • (2022)First Things First? Order Effects in Online Product Recommender SystemsACM Transactions on Computer-Human Interaction10.1145/355788630:1(1-35)Online publication date: 22-Aug-2022
  • (2018)Connecting sellers and buyers on the world's largest inventoryProceedings of the 12th ACM Conference on Recommender Systems10.1145/3240323.3241733(490-491)Online publication date: 27-Sep-2018
  • (2018)Personal Recommendations for Raising Social Eminence in an EnterpriseProceedings of the 23rd International Conference on Intelligent User Interfaces10.1145/3172944.3172956(629-639)Online publication date: 5-Mar-2018
  • (2018)Care to Share?Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining10.1145/3159652.3159713(207-215)Online publication date: 2-Feb-2018
  • (2018)GISTExpert Systems with Applications: An International Journal10.1016/j.eswa.2017.10.03794:C(81-93)Online publication date: 15-Mar-2018
  • (2017)Structuring the UnstructuredProceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3077136.3096469(1351-1351)Online publication date: 7-Aug-2017
  • (2012)Social Recommender SystemsRecommender Systems Handbook10.1007/978-1-0716-2197-4_22(835-870)Online publication date: 24-Feb-2012

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