skip to main content
10.1145/2851581.2892359acmconferencesArticle/Chapter ViewAbstractPublication PageschiConference Proceedingsconference-collections
abstract

Exploring Editorial Content Optimization for Websites through a Statistical Ranking of Articles

Published:07 May 2016Publication History

ABSTRACT

This study describes an online content optimization ranking system for editorial teams. Research on online content optimization has either focused on developing serving schemes for large online news and aggregation websites or complex algorithms for user generated content-based websites. An unexplored area in this domain was the development of a content optimization technique for smaller, editorially-focused sites that creates a long-term brand value that inspires visitors to engage with websites. The results of a study on 276 online articles and associated web metrics show that images within an article, the number of times visitors viewed an article and if they reached the article through a search engine were significant positive predictors of the time they spent with articles. However, the percentage of single-page visits to an article and the number of times visitors clicked a link outside of an article were significant negative predictors for the time they spent with articles. These factors were utilized to develop a statistical rank for content optimization, which shows some initial promising results.

References

  1. Deepak Agarwal, Bee-Chung Chen, Pradheep Elango, Nitin Motgi, Seung-Taek Park, Raghu Ramakrishnan, Scott Roy, and Joe Zachariah. 2007. Online Models for Content Optimization. Advances in Neural Information Processing Systems 21.Google ScholarGoogle Scholar
  2. Vandana Ahuja and Yajulu Medury. 2010. Corporate blogs as e-CRM tools - Building consumer engagement through content management. Journal of Database Marketing & Customer Strategy Management, 17(2), 91-105.Google ScholarGoogle ScholarCross RefCross Ref
  3. Namita Bhatnagar, Lerzan Aksoy, and Selin A. Malkoc. 2004. Embedding Brands Within Media Content: The Impact of Message, Media, and Consumer Characteristics on Placement Efficacy In The Psychology of Entertainment Media: Blurring the Lines Between Entertainment and Persuasion, L. J. Shrum, ed.,Mahwah, NJ: Lawrence Erlbaum, 99-116Google ScholarGoogle Scholar
  4. Abhinandan S. Das, Mayur Datar, Ashutosh Garg, and Shyam Rajaram. 2007. Google News Personalization: Scalable Online Collaborative Filtering. In Proceedings of the 16th International Conference on World Wide Web(WWW '07), 271280. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Robert T. Douglass, Mike Little, and Jared W. Smith. 2005. Building Online Communities With Drupal, phpBB, and WordPress. ISBN: 978--159059--562--6 Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Chetan G. Jain. 2010. The study of open source CMSs. (Order No. 1480203, Rutgers The State University of New Jersey - New Brunswick). ProQuest Dissertations and Theses, 94. Retrieved from http://search.proquest.com/docview/748969671?accountid=6143.Google ScholarGoogle Scholar
  7. Angella J. Kim and Eunjo Ko. 2010. Do social media marketing activities enhance customer equity? An empirical study of luxury fashion brand. Journal of Business Research 65. 1480--1486.Google ScholarGoogle Scholar
  8. Ron Kohavi, Roger Longbotham, Dan Sommerfield, and Randal M. Henne. 2009. Controlled experiments on the web: survey and practical guide. Data Min. Knowl. Discov. 18(1):140-181, ISSN 1384--5810. doi: http://dx.doi.org/10.1007/s10618-008-0114--1 Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Tyler ME, Ledford. 2006. Google Analytics. Wiley, ISBN: 0470053852 Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Janette Lehmann, Mounia Lalmas, Elad Yom-Tov and Georges Dupret. Models of User Engagement. In UMAP'12 Proceedings of the 20th international conference on User Modeling, Adaptation, and Personalization, Montreal, 164 -175. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. MySQL AB. 2004. MySQL,http://www.mysql.com July 15, 2004.Google ScholarGoogle Scholar
  12. Sabine Niederer and Jose Van Dijck. 2010. Wisdom of the crowd or technicity of content? Wikipedia as a sociotechnical system. New Media & Society 12(8): 1368-1387.Google ScholarGoogle ScholarCross RefCross Ref
  13. Chandan (Dan) Sarkar, Donghee Yvette Wohn, Cliff Lampe, and Kurt DeMaagd. 2012. A Quantitative Explanation of Governance in an Online PeerProduction Community. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '2012), 2939 -2942. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. SAS Institute Inc 2015. SAS ® Enterprise Miner? for Desktop. Cary, NC: SAS Institute Inc.Google ScholarGoogle Scholar
  15. Christina Sauper, Regina Barzilay. 2009 Automatically generating Wikipedia articles: A structure-aware approach. In Proceedings of the Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, 208-216. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. George A.F. Seber and Alan J. Lee. 2003. Prediction and Model Selection In Linear Regression Analysis. John Wiley & Sons, Hoboken, NJ, 413--420.Google ScholarGoogle Scholar
  17. Brian Solis. 2010. Engage: The Complete Guide for Brands and Businesses to Build, Cultivate, and Measure Success in the New Web, Hoboken, NJ: Wiley Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Benjamin Spiegel. 2012. The Once and Future King: Editorial or User-Generated Content? Retrieved October 11, 2015 from http://www.searchmarketingstandard.com/theonce-and-future-king-editorial-or-user-generatedcontentGoogle ScholarGoogle Scholar
  19. Debbie Williams. 2011. The Who, What, Where, Why, and How of Editorial Content Strategy. Retrieved January 5, 2016 from http://contentmarketinginstitute.com/2011/01/editorial-content-strategy/Google ScholarGoogle Scholar
  20. Elad Yom-Tov, Mounia Lalmasy, Ricardo BaezaYatesy, Georges Duprety, Janette Lehmanny and Pinar Donmez. Measuring Inter-Site Engagement. In 2013 IEEE Conference on Big Data, 228--236.Google ScholarGoogle Scholar

Index Terms

  1. Exploring Editorial Content Optimization for Websites through a Statistical Ranking of Articles

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      CHI EA '16: Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems
      May 2016
      3954 pages
      ISBN:9781450340823
      DOI:10.1145/2851581

      Copyright © 2016 Owner/Author

      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.

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 7 May 2016

      Check for updates

      Qualifiers

      • abstract

      Acceptance Rates

      CHI EA '16 Paper Acceptance Rate1,000of5,000submissions,20%Overall Acceptance Rate6,164of23,696submissions,26%
    • Article Metrics

      • Downloads (Last 12 months)1
      • Downloads (Last 6 weeks)0

      Other Metrics

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader