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Bronstein, J.; Gazit, T.; Perez, O.; Bar-Ilan, J.; Aharony, N.; Amichai-Hamburger, Y.: ¬An examination of the factors contributing to participation in online social platforms (2016)
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- Abstract
- Purpose The purpose of this paper is to examine participation in online social platforms consisting of information exchange, social network interactions, and political deliberation. Despite the proven benefits of online participation, the majority of internet users read social media data but do not directly contribute, a phenomenon called lurking. Design/methodology/approach A survey was administered electronically to 507 participants and consisted of ten sections in a questionnaire to gather data on the relationship between online participation and the following variables: anonymity, social value orientation, motivations, and participation in offline activities, as well as the internet's political influence and personality traits. Findings Findings show that users with high levels of participation also identify themselves, report higher levels of extroversion, openness, and activity outside the internet, the motivations being an intermediary variable in the relationship between the variables value. Originality/value The study shows that participation in online social platforms is not only related to personality traits, but they are impacted by the nature of the motivations that drive them to participate in the particular social platform, as well as by the interest toward the specific topic, or the type or nature of the social group with whom they are communicating.
- Date
- 20. 1.2015 18:30:22
- Source
- Aslib journal of information management. 68(2016) no.6, S.793-818
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Bar-Ilan, J.: Information hub blogs (2005)
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- Source
- Journal of information science. 31(2005) no.4, S.297-307
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Zhitomirsky-Geffet, M.; Bar-Ilan, J.; Levene, M.: Testing the stability of "wisdom of crowds" judgments of search results over time and their similarity with the search engine rankings (2016)
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- Abstract
- Purpose - One of the under-explored aspects in the process of user information seeking behaviour is influence of time on relevance evaluation. It has been shown in previous studies that individual users might change their assessment of search results over time. It is also known that aggregated judgements of multiple individual users can lead to correct and reliable decisions; this phenomenon is known as the "wisdom of crowds". The purpose of this paper is to examine whether aggregated judgements will be more stable and thus more reliable over time than individual user judgements. Design/methodology/approach - In this study two simple measures are proposed to calculate the aggregated judgements of search results and compare their reliability and stability to individual user judgements. In addition, the aggregated "wisdom of crowds" judgements were used as a means to compare the differences between human assessments of search results and search engine's rankings. A large-scale user study was conducted with 87 participants who evaluated two different queries and four diverse result sets twice, with an interval of two months. Two types of judgements were considered in this study: relevance on a four-point scale, and ranking on a ten-point scale without ties. Findings - It was found that aggregated judgements are much more stable than individual user judgements, yet they are quite different from search engine rankings. Practical implications - The proposed "wisdom of crowds"-based approach provides a reliable reference point for the evaluation of search engines. This is also important for exploring the need of personalisation and adapting search engine's ranking over time to changes in users preferences. Originality/value - This is a first study that applies the notion of "wisdom of crowds" to examine an under-explored in the literature phenomenon of "change in time" in user evaluation of relevance.
- Date
- 20. 1.2015 18:30:22
- Source
- Aslib journal of information management. 68(2016) no.4, S.407-427
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Bar-Ilan, J.; Gutman,T.: How do search engines respond to some non-English queries? (2005)
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- Source
- Journal of information science. 31(2005) no.1, S.13-
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Bar-Ilan, J.; Zhitomirsky-Geffet, M.; Miller, Y.; Shoham, S.: ¬The effects of background information and social interaction on image tagging (2010)
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- Abstract
- In this article, we describe the results of an experiment designed to understand the effects of background information and social interaction on image tagging. The participants in the experiment were asked to tag 12 preselected images of Jewish cultural heritage. The users were partitioned into three groups: the first group saw only the images with no additional information whatsoever, the second group saw the images plus a short, descriptive title, and the third group saw the images, the titles, and the URL of the page in which the image appeared. In the first stage of the experiment, each user tagged the images without seeing the tags provided by the other users. In the second stage, the users saw the tags assigned by others and were encouraged to interact. Results show that after the social interaction phase, the tag sets converged and the popular tags became even more popular. Although in all cases the total number of assigned tags increased after the social interaction phase, the number of distinct tags decreased in most cases. When viewing the image only, in some cases the users were not able to correctly identify what they saw in some of the pictures, but they overcame the initial difficulties after interaction. We conclude from this experiment that social interaction may lead to convergence in tagging and that the wisdom of the crowds helps overcome the difficulties due to the lack of information.
- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.5, S.940-951
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Bar-Ilan, J.: Methods for measuring search engine performance over time (2002)
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- Source
- Journal of the American Society for Information Science and technology. 53(2002) no.4, S.308-319
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Bar-Ilan, J.; Keenoy, K.; Yaari, E.; Levene, M.: User rankings of search engine results (2007)
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- Abstract
- In this study, we investigate the similarities and differences between rankings of search results by users and search engines. Sixty-seven students took part in a 3-week-long experiment, during which they were asked to identify and rank the top 10 documents from the set of URLs that were retrieved by three major search engines (Google, MSN Search, and Yahoo!) for 12 selected queries. The URLs and accompanying snippets were displayed in random order, without disclosing which search engine(s) retrieved any specific URL for the query. We computed the similarity of the rankings of the users and search engines using four nonparametric correlation measures in [0,1] that complement each other. The findings show that the similarities between the users' choices and the rankings of the search engines are low. We examined the effects of the presentation order of the results, and of the thinking styles of the participants. Presentation order influences the rankings, but overall the results indicate that there is no "average user," and even if the users have the same basic knowledge of a topic, they evaluate information in their own context, which is influenced by cognitive, affective, and physical factors. This is the first large-scale experiment in which users were asked to rank the results of identical queries. The analysis of the experimental results demonstrates the potential for personalized search.
- Source
- Journal of the American Society for Information Science and Technology. 58(2007) no.9, S.1254-1266
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Lazinger, S.S.; Bar-Ilan, J.; Peritz, B.C.: Internet use by faculty members in various disciplines : a comparative case study (1997)
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- Source
- Journal of the American Society for Information Science. 48(1997) no.6, S.508-518
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Bar-Ilan, J.: Evaluating the stability of the search tools Hotbot and Snap : a case study (2000)
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- Source
- Online information review. 24(2000) no.6, S.439-449
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Shema, H.; Bar-Ilan, J.; Thelwall, M.: Do blog citations correlate with a higher number of future citations? : Research blogs as a potential source for alternative metrics (2014)
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- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.5, S.1018-1027
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Bar-Ilan, J.; Keenoy, K.; Levene, M.; Yaari, E.: Presentation bias is significant in determining user preference for search results : a user study (2009)
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- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.1, S.135-149
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Shema, H.; Bar-Ilan, J.; Thelwall, M.: How is research blogged? : A content analysis approach (2015)
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- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.6, S.1136-1149
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Zhitomirsky-Geffet, M.; Bar-Ilan, J.; Levene, M.: Categorical relevance judgment (2018)
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- Source
- Journal of the Association for Information Science and Technology. 69(2018) no.9, S.1084-1094
