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Sponsored vs. Organic (Research Paper) Recommendations and the Impact of Labeling

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8092))

Abstract

In this paper we show that organic recommendations are preferred over commercial recommendations even when they point to the same freely downloadable research papers. Simply the fact that users perceive recommendations as commercial decreased their willingness to accept them. It is further shown that the exact labeling of recommendations matters. For instance, recommendations labeled as ‘advertisement’ performed worse than those labeled as ‘sponsored’. Similarly, recommendations labeled as ‘Free Research Papers’ performed better than those labeled as ‘Research Papers’. However, whatever the differences between the labels were – the best performing recommendations were those with no label at all.

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References

  1. Manchanda, P., Dubé, J.P., Goh, K.Y., Chintagunta, P.K.: The effect of banner advertising on internet purchasing. Journal of Marketing Research 43 (2006)

    Google Scholar 

  2. Schwartz, B.: Google AdWords Click Through Rates: 2% is Average But Double Digits is Great. Search Engine Round Table Blog (2010), http://www.seroundtable.com/archives/021514.html

  3. Gori, M., Pucci, A.: Research paper recommender systems: A random-walk based approach. In: Proceedings of the International Conference on Web Intelligence (2006)

    Google Scholar 

  4. Zhang, M., Wang, W., Li, X.: A Paper Recommender for Scientific Literatures Based on Semantic Concept Similarity. In: Buchanan, G., Masoodian, M., Cunningham, S.J. (eds.) ICADL 2008. LNCS, vol. 5362, pp. 359–362. Springer, Heidelberg (2008)

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  5. Beel, J., Langer, S., Genzmehr, M., Nürnberger, A.: Introducing Docear’s Research Paper Recommender System. In: Proceedings of the ACM/IEEE Joint Conference on Digital Libraries, JCDL (2013)

    Google Scholar 

  6. Beel, J., Gipp, B., Langer, S., Genzmehr, M.: Docear: An Academic Literature Suite for Searching, Organizing and Creating Academic Literature. In: Proceedings of the 11th ACM/IEEE Joint Conference on Digital Libraries, pp. 465–466. ACM (2011)

    Google Scholar 

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© 2013 Springer-Verlag Berlin Heidelberg

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Beel, J., Langer, S., Genzmehr, M. (2013). Sponsored vs. Organic (Research Paper) Recommendations and the Impact of Labeling. In: Aalberg, T., Papatheodorou, C., Dobreva, M., Tsakonas, G., Farrugia, C.J. (eds) Research and Advanced Technology for Digital Libraries. TPDL 2013. Lecture Notes in Computer Science, vol 8092. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40501-3_44

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  • DOI: https://doi.org/10.1007/978-3-642-40501-3_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40500-6

  • Online ISBN: 978-3-642-40501-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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