Characteristics analysis and evaluation of discourse leading for academic journals: perspectives from multiple integration of altmetrics indicators and evaluation methods

Wang, Xu

doi:10.1108/lht-04-2022-0195

Cited by 13 publications

(11 citation statements)

References 71 publications

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“…Readers may be interested in some related articles on whether authors play fair or manipulate Google Scholar bibliometric indicators, such as h-index and i10-index (Loan and Shah, 2022), and the analysis of Sci-Hub use with Google Trends (Behboudi et al ., 2021); Chen et al . (2021) studied the effect of interdisciplinary components' citation intensity on scientific impact, whether proceedings papers in science fields have higher impacts than those in social science and humanities (Yang and Qi, 2021), characteristics analysis and evaluation of discourse leading for academic journals (Wang, 2022), the ecosystem of research tools for scholarly communication (Rao et al ., 2022), the scientific outcome in the domain of grey literature (Wani and Ganaie, 2022), early discovering highly cited academic papers (Tang et al ., 2023) and textbook citations (Maleki et al ., 2023).…”

Section: Bibliometric Analytics For Academic Rankingmentioning

confidence: 99%

Editorial: Special selection on contemporary bibliometric analytics

Chiu

2023

LHT

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Section: Bibliometric Analytics For Academic Rankingmentioning

confidence: 99%

Editorial: Special selection on contemporary bibliometric analytics

Chiu

2023

LHT

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“…The evaluation of academic journals must be based on specific characteristics of journals outlined by their subject, content, dissemination medium, object and implementation effect. These characteristics highlight the three crucial aspects of academic journals: influence, communication and leadership (Zhao et al , 2022; Wang, 2022). In this study, the three features of journals – namely, their influence, communication power and novelty – are evaluated through a three-dimensional framework.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Meanwhile, Zhang et al (2019) devised journal evaluation dimensions and indicators according to academic quality, influence and popularity. Additionally, multidimensional, multi-indicator and multi-method fusion analysis was used by Wang (2022), who aggregated multi-source heterogeneous data and used correlation analysis, integrated factor analysis, entropy weighting, the TOPSIS method and the two-dimensional four-quadrant mapping method. Journal evaluation is tackled from a diverse range of research perspectives that covers many dimensions, from single (Balatsky et al , 2021) to multidisciplinary (Han and Qiu, 2022) and cross-disciplinary analyses (Zhang et al , 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Journal evaluation is tackled from a diverse range of research perspectives that covers many dimensions, from single (Balatsky et al , 2021) to multidisciplinary (Han and Qiu, 2022) and cross-disciplinary analyses (Zhang et al , 2019). Traditional journals (Zheng et al , 2019) to open access publication (Wei, 2020), static (Hao and Li, 2019) to dynamic evaluation (Ma et al , 2022) and single factor (Abramo et al , 2023) to multidimensional information measurement (Wang, 2022), all have relevant studies regarding journal evaluation.…”

Section: Literature Reviewmentioning

confidence: 99%

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Research on the evaluation of academic journals from a multidimensional fusion measurement perspective

Rong

Zhu

2023

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Purpose This paper aims to conduct a comprehensive analysis to evaluate the current situation of journals, examine the factors that influence their development, and establish an evaluation index system and model. The objective is to enhance the theory and methodologies used for journal evaluation and provide guidance for their positive development. Design/methodology/approach This study uses empirical data from economics journals to analyse their evaluation dimensions, methods, index system and evaluation framework. This study then assigns weights to journal data using single and combined evaluations in three dimensions: influence, communication and novelty. It calculates several evaluation metrics, including the explanation rate, information entropy value, difference coefficient and novelty degree. Finally, this study applies the concept of fuzzy mathematics to measure the final results. Findings The use of affiliation degree and fuzzy Borda number can synthesize ranking and score differences among evaluation methods. It combines internal objective information and improves model accuracy. The novelty of journal topics positively correlates with both the journal impact factor and social media mentions. In addition, journal communication power indicators compensate for the shortcomings of traditional citation analysis. Finally, the three-dimensional representative evaluation index serves as a reminder to academic journals to avoid the vortex of the Matthew effect. Originality/value This paper proposes a journal evaluation model comprising academic influence, communication power and novelty dimensions. It uses fuzzy Borda evaluation to address issues related to the weighing of single evaluation methods. This study also analyses the relationship of the three dimensions and offers insights for journal development in the new media era.

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“…Users can not only form Q&A links with each other but also interact through social behaviours, such as liking, following and sharing (Feng et al , 2022; Wang and Feng, 2022), which attracts more and more people to participate in the process of knowledge dissemination and sharing. The efficiency of knowledge sharing has been greatly improved, and the total amount of knowledge has grown exponentially (Wang, 2022a, 2022b). With the continuous replacement and connection of old and new knowledge, the knowledge network system has become more complex (Teng et al , 2017).…”

Section: Introductionmentioning

confidence: 99%

Analysis of the characteristics and evolution of knowledge label networks in the Q&A community: taking the Zhihu platform as an example

Feng

Wang

Xue

et al. 2023

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Purpose In the era of mobile internet, the social Q&A community has built a large-scale and complex knowledge label network through its internal knowledge units, and the scale and structure of the network have changed over time. By analysing the structural characteristics and evolution rules of knowledge label networks, the main purpose of this study is to understand the internal mechanisms of the replacement of old and new knowledge and the expansion of knowledge element boundaries, so as to explore the realization path of knowledge management in the new era from the perspective of complex networks. Design/methodology/approach This paper uses distributed crawlers to capture 419,349 samples from the Zhihu platform. Each sample contains 33 characteristic dimensions, and the natural year is used as the sliding window to divide the whole. In this study, the global knowledge label network and 11 local knowledge label networks are first constructed. Then, the degree distribution analysis and central node exploration of the knowledge label network are carried out using the complex network method. Finally, the average shortest path and average clustering coefficient of the network are analysed by the time series method, and the ARIMA model is used to predict the evolution of the correlation coefficient. Findings The research results show that the dissimilation degree of the degree distribution of the knowledge label network has gradually decreased from 2011 to 2021, and the attention of users in the knowledge community has shown a trend of distraction and diversification over time. With the expansion of the scale of the knowledge label network and the transformation to an information network, the network sparsity is becoming more and more obvious, and the knowledge granularity of the Q&A community is being refined and diversified. The prediction of the correlation coefficient of the knowledge label network by the ARIMA model shows that the connection between the labels is lacking diversity and the opinion strengthening phenomenon tends to strengthen, which is more likely to form the “echo chamber effect”, resulting in mutual isolation and even opposition between different circles. The Q&A community is about to enter a mature stage, and the corresponding status of each label has been finalized. The future development trend of label networks will be reflected in the substitution between labels, and the specific structure will not change significantly. Originality/value The Q&A community model is the trend in Web 2.0 community development. This study proves the effectiveness of complex networks and time series prediction methods in knowledge label network mining in the Q&A community.

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Characteristics analysis and evaluation of discourse leading for academic journals: perspectives from multiple integration of altmetrics indicators and evaluation methods

Cited by 13 publications

References 71 publications

Editorial: Special selection on contemporary bibliometric analytics

Editorial: Special selection on contemporary bibliometric analytics

Research on the evaluation of academic journals from a multidimensional fusion measurement perspective

Analysis of the characteristics and evolution of knowledge label networks in the Q&A community: taking the Zhihu platform as an example

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