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Zhitomirsky-Geffet, M.; Erez, E.S.; Bar-Ilan, J.: Toward multiviewpoint ontology construction by collaboration of non-experts and crowdsourcing : the case of the effect of diet on health (2017)
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- Abstract
- Domain experts are skilled in buliding a narrow ontology that reflects their subfield of expertise based on their work experience and personal beliefs. We call this type of ontology a single-viewpoint ontology. There can be a variety of such single viewpoint ontologies that represent a wide spectrum of subfields and expert opinions on the domain. However, to have a complete formal vocabulary for the domain they need to be linked and unified into a multiviewpoint model while having the subjective viewpoint statements marked and distinguished from the objectively true statements. In this study, we propose and implement a two-phase methodology for multiviewpoint ontology construction by nonexpert users. The proposed methodology was implemented for the domain of the effect of diet on health. A large-scale crowdsourcing experiment was conducted with about 750 ontological statements to determine whether each of these statements is objectively true, viewpoint, or erroneous. Typically, in crowdsourcing experiments the workers are asked for their personal opinions on the given subject. However, in our case their ability to objectively assess others' opinions was examined as well. Our results show substantially higher accuracy in classification for the objective assessment approach compared to the results based on personal opinions.
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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.
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Shema, H.; Bar-Ilan, J.; Thelwall, M.: How is research blogged? : A content analysis approach (2015)
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- Abstract
- Blogs that cite academic articles have emerged as a potential source of alternative impact metrics for the visibility of the blogged articles. Nevertheless, to evaluate more fully the value of blog citations, it is necessary to investigate whether research blogs focus on particular types of articles or give new perspectives on scientific discourse. Therefore, we studied the characteristics of peer-reviewed references in blogs and the typical content of blog posts to gain insight into bloggers' motivations. The sample consisted of 391 blog posts from 2010 to 2012 in Researchblogging.org's health category. The bloggers mostly cited recent research articles or reviews from top multidisciplinary and general medical journals. Using content analysis methods, we created a general classification scheme for blog post content with 10 major topic categories, each with several subcategories. The results suggest that health research bloggers rarely self-cite and that the vast majority of their blog posts (90%) include a general discussion of the issue covered in the article, with more than one quarter providing health-related advice based on the article(s) covered. These factors suggest a genuine attempt to engage with a wider, nonacademic audience. Nevertheless, almost 30% of the posts included some criticism of the issues being discussed.
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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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- Abstract
- Journal-based citations are an important source of data for impact indices. However, the impact of journal articles extends beyond formal scholarly discourse. Measuring online scholarly impact calls for new indices, complementary to the older ones. This article examines a possible alternative metric source, blog posts aggregated at ResearchBlogging.org, which discuss peer-reviewed articles and provide full bibliographic references. Articles reviewed in these blogs therefore receive "blog citations." We hypothesized that articles receiving blog citations close to their publication time receive more journal citations later than the articles in the same journal published in the same year that did not receive such blog citations. Statistically significant evidence for articles published in 2009 and 2010 support this hypothesis for seven of 12 journals (58%) in 2009 and 13 of 19 journals (68%) in 2010. We suggest, based on these results, that blog citations can be used as an alternative metric source.
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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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- Date
- 20. 1.2015 18:30:22
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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
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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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- Date
- 20. 1.2015 18:30:22
