Web analytics of user path tracing and a novel algorithm for generating recommendations in Open Journal Systems

Taraghi, Behnam; Grossegger, Martin; Ebner, Martin; Holzinger, Andreas

doi:10.1108/oir-09-2012-0152

Cited by 10 publications

(9 citation statements)

References 36 publications

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“…Most recommendation systems work based on users' preferences (Pazzani and Billsus, 2007) or activity patterns (Taraghi et al, 2013). However, they are not always tailored to filter out suspicious entries.…”

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confidence: 99%

A theoretical framework to identify authentic online reviews

Banerjee

Chua

2014

Online Information Review

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Purpose -The purpose of this paper is to investigate the extent to which textual characteristics of online reviews help identify authentic entries from manipulative ones across positive and negative comments. Design/methodology/approach -A theoretical framework is proposed to identify authentic online reviews from manipulative ones based on three textual characteristics, namely, comprehensibility, informativeness, and writing style. The framework is tested using two publicly available data sets, one comprising positive reviews to hype own offerings, and the other including negative reviews to slander competing offerings. Logistic regression is used for analysis. Findings -The three textual characteristics offered useful insights to identify authentic online reviews from manipulative ones. In particular, the differences between authentic and manipulative reviews in terms of comprehensibility and informativeness were more conspicuous for negative entries. On the other hand, the differences between authentic and manipulative reviews in terms of writing style were more conspicuous for positive entries.Research limitations/implications -The findings of this paper are somewhat constrained by the scope of the data sets used for analysis. Originality/value -The paper represents one of the earliest attempts to develop a theoretical framework to identify authentic online reviews. Prior research has shed light on ways to classify reviews as authentic or manipulative. However, literature on specific differences between the two in terms of textual characteristics is relatively limited. Moreover, by suggesting differences between authentic and manipulative reviews across positive and negative comments, the findings offer nuanced insights into a research area that is growing in importance.

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confidence: 99%

A theoretical framework to identify authentic online reviews

Banerjee

Chua

2014

Online Information Review

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“…Compared with event detection that focuses more on issue description, opinion mining concerns more about public opinions toward certain topics. Taraghi et al (2013) addressed problem about the recommendation of appropriate relevant work from an increasing amount of scientific literatures. They introduced a recommender system, in which the analysis of user paths, i.e.…”

Section: Literature Reviewmentioning

confidence: 99%

A bibliometric analysis of event detection in social media

Chen

Wang

Tang

et al. 2019

OIR

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Purpose The purpose of this paper is to explore the research status and development trend of the field of event detection in social media (ED in SM) through a bibliometric analysis of academic publications. Design/methodology/approach First, publication distributions are analyzed including the trends of publications and citations, subject distribution, predominant journals, affiliations, authors, etc. Second, an indicator of collaboration degree is used to measure scientific connective relations from different perspectives. A network analysis method is then applied to reveal scientific collaboration relations. Furthermore, based on keyword co-occurrence analysis, major research themes and their evolutions throughout time span are discovered. Finally, a network analysis method is applied to visualize the analysis results. Findings The area of ED in SM has received increasing attention and interest in academia with Computer Science and Engineering as two major research subjects. The USA and China contribute the most to the area development. Affiliations and authors tend to collaborate more with those within the same country. Among the 14 identified research themes, newly emerged themes such as Pharmacovigilance event detection are discovered. Originality/value This study is the first to comprehensively illustrate the research status of ED in SM by conducting a bibliometric analysis. Up-to-date findings are reported, which can help relevant researchers understand the research trend, seek scientific collaborators and optimize research topic choices.

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“…Some key examples for these examined aspects are: relating authorship patterns with innovation (He et al, 2013;Lungeanu and Contractor, 2015), summarizing best practices in scientific collaboration, and making recommendations for institutional cooperation (Parada et al, 2013), recommendations for cooperation within specific academic fields (Holzinger et al, 2013;Velden and Lagoze, 2009;Xu et al, 2014;Cheong and Corbitt, 2009), or for interdisciplinary collaboration (Valdez et al, 2014). Some scholars have further enhanced these type of studies, and tried to use CAN to infer about researchers' research impact (Ortega, 2014), to determine their future publication likelihood (Kurosawa and Takama, 2012), for generating article recommendation systems (Taraghi et al, 2013), and to define the collaboration potential between authors (Giuliani et al, 2010).…”

Section: Relevant Literaturesmentioning

confidence: 99%

A typology of collaborative research networks

Hayat

2017

OIR

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Purpose Many studies have investigated how the structure of the collaborative networks of researchers influences the nature of their work, and its outcome. Co-authorship networks (CANs) have been widely looked at as proxies that can help bring understanding to the structure of research collaborative ties. The purpose of this paper is to provide a framework for describing what influences the formation of different research collaboration patterns. Design/methodology/approach The authors use social network analysis (SNA) to analyze the co-authorship ego networks of the ten most central authors in 24 years of papers (703 papers and 1,118 authors) published in the Proceedings of CASCON, a computer science conference. In order to understand what lead to the formation of the different CANs the authors examined, the authors conducted semi-structured interviews with these authors. Findings Based on this examination, the authors propose a typology that differentiates three styles of co-authorship: matchmaking, brokerage, and teamwork. The authors also provide quantitative SNA-based measures that can help place researchers’ CAN into one of these proposed categories. Given that many different network measures can describe the collaborative network structure of researchers, the authors believe it is important to identify specific network structures that would be meaningful when studying research collaboration. The proposed typology can offer guidance in choosing the appropriate measures for studying research collaboration. Originality/value The results presented in this paper highlight the value of combining SNA analysis with interviews when studying CAN. Moreover, the results show how co-authorship styles can be used to understand the mechanisms leading to the formation of collaborative ties among researchers. The authors discuss several potential implications of these findings for the study of research collaborations.

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Web analytics of user path tracing and a novel algorithm for generating recommendations in Open Journal Systems

Cited by 10 publications

References 36 publications

A theoretical framework to identify authentic online reviews

A theoretical framework to identify authentic online reviews

A bibliometric analysis of event detection in social media

A typology of collaborative research networks

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