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Triggers and connection-making for serendipity via user interface in recommender systems

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Abstract

This paper reports on the use of transparency in recommender a system that facilitates serendipitous encounters for users. Currently, there are serendipitous recommender systems that facilitate serendipitous encounters; however, there are no studies on the connection-making process or on the process of achieving connection-making through a user interface design. Adding to our previous work on connection-making and serendipity-facilitating recommender systems, we examine transparency in recommender systems as it relates to connection-making we studied transparency of recommendations to foster connection-making. This study is novel as it introduces a new user interface design for recommender system in academia and new study methods and approaches and studies a large group of users who are using this recommender system. The user interface components such as bubble messages on recommender system mechanism, user controls on manipulating the recommender system outcomes and showing authors work addition to recommendation. Repeated measure design of research was used to study serendipity and task load among users for Google Scholar and JabRef related work user interface (User interface developed for Experiment). Subjective evaluation of user interface was done along with NASA-Task Load Index for workload measurement. Further sentiment analysis was conducted for validations of findings. Our study finds that serendipitous recommendations and user satisfaction is facilitated via transparency in recommender systems. Furthermore, we found that transparency enhances interactivity for users who are looking for novel and useful recommendations related to their work. This work contributes to human computer interaction studies of recommender systems and reviews the leading literature on transparency, serendipity, and recommender systems in learning environments.

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Acknowledgments

The authors would like to extend their appreciation to Zayed University, UAE, for funding this research under the Cluster Research Grant # R17075.

The authors would like to extend their appreciation to Institute of Management Sciences, Peshawar, Pakistan.

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Authors and Affiliations

  1. Centre for Excellence in Information Technology, Institute of Management Sciences, Peshawar, Pakistan

    Ahmad Hassan Afridi

  2. Zayed University, Dubai, UAE

    Fatma Outay

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  1. Ahmad Hassan Afridi
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Correspondence to Ahmad Hassan Afridi.

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ANNEXTURE

ANNEXTURE

Users Comments for the User Interface Improvements for JabRef-related Work Tab Developed for This Experiment.

  • User interface is very helpful and informative for researchers and schools, but I suggest toadd an option at year wise recommendation. User interface data was highly helpful

  • User interface is good but should be more clear,self-explanatory

  • The user interface is simple and graphic support product is efficient

  • Simple UI, need color change and click count, and paper clicked portion can be at the bottom of UI. The data suggested were seems useful to use

  • It’s good. UI is good, search should be more wide

  • Filter feature, future work not showing

  • He has put some pages work on a single platform it’s more helpful for research field. Beautifully arranged, very impressive

  • The UI is overall good, if there is a filter by year by research field that would be more user-friendly

  • It is a productive software

  • Color theme is a bit dull, otherwise it’s good. Interface is a bit scattered

  • The interface is better and easy to use. I think you need to add at least 10 papers at a time to see in reviews, which is related to key

  • The graph is easy to understand, shows more detail about the research. Interfaces are good, show research paper recommendations

  • To the point, interesting graphs, easy to use, colors are little dull. 7 m time taken, 1 page viewed

  • All type of graphical things can be displayed on it, easier to get related documents. Make a graph to explore the author profile which is based on citation

  • Filter must be included,conclusion of articles, too dark, it must be brighter so it should be clearly visible

  • User-friendly. Is easy should also have conclusion. Charts in bar are friendly

  • Interface is good but need some color changes and titles for charts

  • Color themes used are hard which creates visibility problems. It’s possible the contents should be covered in available screen site rather than scrolling

  • Search field is required

  • Good, but if the search paper will categorize into 3 to 4 stages like abstract, introduction, explanation or working and conclusion individually

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Afridi, A.H., Outay, F. Triggers and connection-making for serendipity via user interface in recommender systems. Pers Ubiquit Comput 25, 77–92 (2021). https://doi.org/10.1007/s00779-020-01371-w

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