Search (7 results, page 1 of 1)

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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

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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.

Theme

Social tagging

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Abstract

Purpose - Ontologies are prone to wide semantic variability due to subjective points of view of their composers. The purpose of this paper is to propose a new approach for maximal unification of diverse ontologies for controversial domains by their relations. Design/methodology/approach - Effective matching or unification of multiple ontologies for a specific domain is crucial for the success of many semantic web applications, such as semantic information retrieval and organization, document tagging, summarization and search. To this end, numerous automatic and semi-automatic techniques were proposed in the past decade that attempt to identify similar entities, mostly classes, in diverse ontologies for similar domains. Apparently, matching individual entities cannot result in full integration of ontologies' semantics without matching their inter-relations with all other-related classes (and instances). However, semantic matching of ontological relations still constitutes a major research challenge. Therefore, in this paper the authors propose a new paradigm for assessment of maximal possible matching and unification of ontological relations. To this end, several unification rules for ontological relations were devised based on ontological reference rules, and lexical and textual entailment. These rules were semi-automatically implemented to extend a given ontology with semantically matching relations from another ontology for a similar domain. Then, the ontologies were unified through these similar pairs of relations. The authors observe that these rules can be also facilitated to reveal the contradictory relations in different ontologies. Findings - To assess the feasibility of the approach two experiments were conducted with different sets of multiple personal ontologies on controversial domains constructed by trained subjects. The results for about 50 distinct ontology pairs demonstrate a good potential of the methodology for increasing inter-ontology agreement. Furthermore, the authors show that the presented methodology can lead to a complete unification of multiple semantically heterogeneous ontologies. Research limitations/implications - This is a conceptual study that presents a new approach for semantic unification of ontologies by a devised set of rules along with the initial experimental evidence of its feasibility and effectiveness. However, this methodology has to be fully automatically implemented and tested on a larger dataset in future research. Practical implications - This result has implication for semantic search, since a richer ontology, comprised of multiple aspects and viewpoints of the domain of knowledge, enhances discoverability and improves search results. Originality/value - To the best of the knowledge, this is the first study to examine and assess the maximal level of semantic relation-based ontology unification.

Date

20. 1.2015 18:30:22

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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

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Abstract

Examines and compares the use of the Internet among various sectors of the faculty at the Hebrew University of Jerusalem, Israel, in order to verify the influence of a number of parameters on this use. Questionnaires were sent to faculty members in all departments and professional schools of the Hebrew University of Jerusalem, a total population of 918 for both the pilot project and the main study. Results indicated that Internet use is consistently higher among faculty members in the sciences and agriculture than among those in the humanities or social sciences. Makes suggestions for training the level of Internet use among the various disciplines of the faculty

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Abstract

The Web is an enormous set of documents connected through hypertext links created by authors of Web pages. These links have been studied quantitatively, but little has been done so far in order to understand why these links are created. As a first step towards a better understanding, we propose a classification of link types in academic environments on the Web. The classification is multi-faceted and involves different aspects of the source and the target page, the link area and the relationship between the source and the target. Such classification provides an insight into the diverse uses of hypertext links on the Web, and has implications for browsing and ranking in IR systems by differentiating between different types of links. As a case study we classified a sample of links between sites of Israeli academic institutions.

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Abstract

Informetrics is a subfield of information science and it encompasses bibliometrics, scientometrics, cybermetrics, and webometrics. This encyclopedia entry provides an overview of informetrics and its subfields. In general, informetrics deals with quantitative aspects of information: its production, dissemination, evaluation, and use. Bibliometrics and scientometrics study scientific literature: papers, journals, patents, and citations; while in webometric studies the sources studied are Web pages and Web sites, and citations are replaced by hypertext links. The entry introduces major topics in informetrics: citation analysis and citation related studies, the journal impact factor, the recently defined h-index, citation databases, co-citation analysis, open access publications and its implications, informetric laws, techniques for mapping and visualization of informetric phenomena, the emerging subfields of webometrics, cybermetrics and link analysis, and research evaluation.