-
Zhitomirsky-Geffet, M.; Bar-Ilan, J.: Towards maximal unification of semantically diverse ontologies for controversial domains (2014)
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- Date
- 20. 1.2015 18:30:22
- Source
- Aslib journal of information management. 66(2014) no.5, S.494-518
-
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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- Date
- 20. 1.2015 18:30:22
-
Bar-Ilan, J.; Peritz, B.C.: Evolution, continuity, and disappearance of documents on a specific topic an the Web : a longitudinal study of "informetrics" (2004)
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- Abstract
- The present paper analyzes the changes that occurred to a set of Web pages related to "informetrics" over a period of 5 years between June 1998 and June 2003. Four times during this time span, in 1998,1999, 2002, and 2003, we monitored previously located pages and searched for new ones related to the topic. Thus, we were able to study the growth of the topic, white analyzing the rates of change and disappearance. The results indicate that modification, disappearance, and resurfacing cannot be ignored when studying the structure and development of the Web.
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Bar-Ilan, J.: ¬The Web as an information source on informetrics? : A content analysis (2000)
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- Source
- Journal of the American Society for Information Science. 51(2000) no.5, S.432-443
-
Bar-Ilan, J.: Informetrics (2009)
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- Date
- 5. 8.2010 17:33:43
-
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
-
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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- Date
- 20. 1.2015 18:30:22
-
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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- Source
- Journal of the American Society for Information Science and Technology. 61(2010) no.5, S.940-951
-
Bergman, O.; Gradovitch, N.; Bar-Ilan, J.; Beyth-Marom, R.: Folder versus tag preference in personal information management (2013)
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- Abstract
- Users' preferences for folders versus tags was studied in 2 working environments where both options were available to them. In the Gmail study, we informed 75 participants about both folder-labeling and tag-labeling, observed their storage behavior after 1 month, and asked them to estimate the proportions of different retrieval options in their behavior. In the Windows 7 study, we informed 23 participants about tags and asked them to tag all their files for 2 weeks, followed by a period of 5 weeks of free choice between the 2 methods. Their storage and retrieval habits were tested prior to the learning session and, after 7 weeks, using special classification recording software and a retrieval-habits questionnaire. A controlled retrieval task and an in-depth interview were conducted. Results of both studies show a strong preference for folders over tags for both storage and retrieval. In the minority of cases where tags were used for storage, participants typically used a single tag per information item. Moreover, when multiple classification was used for storage, it was only marginally used for retrieval. The controlled retrieval task showed lower success rates and slower retrieval speeds for tag use. Possible reasons for participants' preferences are discussed.
-
Zhitomirsky-Geffet, M.; Bar-Ilan, J.; Levene, M.: Analysis of change in users' assessment of search results over time (2017)
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- Source
- Journal of the Association for Information Science and Technology. 68(2017) no.5, S.1137-1148
-
Zhitomirsky-Geffet, M.; Bar-Ilan, J.; Levene, M.: Categorical relevance judgment (2018)
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- Abstract
- In this study we aim to explore users' behavior when assessing search results relevance based on the hypothesis of categorical thinking. To investigate how users categories search engine results, we perform several experiments where users are asked to group a list of 20 search results into several categories, while attaching a relevance judgment to each formed category. Moreover, to determine how users change their minds over time, each experiment was repeated three times under the same conditions, with a gap of one month between rounds. The results show that on average users form 4-5 categories. Within each round the size of a category decreases with the relevance of a category. To measure the agreement between the search engine's ranking and the users' relevance judgments, we defined two novel similarity measures, the average concordance and the MinMax swap ratio. Similarity is shown to be the highest for the third round as the users' opinion stabilizes. Qualitative analysis uncovered some interesting points that users tended to categories results by type and reliability of their source, and particularly, found commercial sites less trustworthy, and attached high relevance to Wikipedia when their prior domain knowledge was limited.
