Objective information retrieval and information literacy

  • Background:


    Over the past three decades, information has become far more accessible due to the advances of digital technology and, in particular, the rapid growth of the internet. By now information is one of the most important resource in our knowledge driven society. As a result, our dependency on systems that help to locate and retrieve information is constantly growing. Using web search engines like Google or Bing has become an essential part of our daily routine. Especially in professional settings (e.g., journalism, scientific research, politics, or exchange trade) reliance on information retrieval systems has increased dramatically. However, the market dominance of a relative small number of system providers combined with their often nontransparent retrieval processes and users’ nonreflective search behavior facilitates accidental or deliberate manipulations through mis-, dis-, and mal-information with severe consequences. Objective information retrieval is therefore an important challenge for both practice and research, that deals with issues ranging from information literacy (i.e., user’s ability to locate, evaluate, and effectively use information for an issue or problem at hand) to the design of innovative information systems enabling transparent information searches.




    Possible topics include but are not limited to: 


    • Empirical investigation of information needs, search behaviour, and/or information literacy in different search contexts - Adaptive search interface design for different levels of information literacy
    • Metrics and methods for assessing the quality of information retrieval systems (e.g., web search engines and scientific literature databases)
    • Design and development of innovative features and search interfaces for creating relevant search requests based on users’ information needs
    • Design and development of methods or system features for effective presentation of retrieved information (e.g., topical clustering, content analysis, reports, text network analysis, graphical representations)
    • Methodological analysis of different information search approaches.


    This is an umbrella topic since topics of interest change rapidly. A specific topic will be refined during a first meeting.


    Introductory literature:


    • Antoniou, D., Plegas, Y., Tsakalidis, A., Tzimas, G., & Viennas, E. (2012). Dynamic refinement of search engines results utilizing the user intervention. Journal of Systems and Software, 85(7), 1577-1587. 
    • Giustini, D., & Kamel Boulos, M. N. (2013). Google Scholar is not enough to be used alone for systematic reviews. Online Journal of Public Health Informatics, 5(2), 1-10. Post, S. (2014). 
    • Scientific objectivity in journalism? How journalists and academics define objectivity, assess its attainability, and rate its desirability. Journalism, 16(6), 730-749. 
    • Shenton, A. K., & Hay-Gibson, N. V. (2012). Information behaviour meta-models. Library Review, 61(2), 92-109. 
    • Sturm, B., & Sunyaev, A. (2017). You Can’t Make Bricks Without Straw: Designing Systematic Literature Search Systems. Paper presented at the Proceedings of the 38th International Conference on Information Systems (ICIS 2017), Seoul, South Korea. 
    • Wilson, T. D. (1997). Information Behaviour: An Interdisciplinary Perspective. Information Processing & Management, 33(4), 551-572.