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Article
Publication date: 3 October 2022

Zheng Wang, Ying Ji, Tao Zhang, Yuanming Li, Lun Wang and Shaojian Qu

With the continuous development of online shopping, analyzing the competitiveness of products in the fierce market competition is becoming increasingly crucial to position their…

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Abstract

Purpose

With the continuous development of online shopping, analyzing the competitiveness of products in the fierce market competition is becoming increasingly crucial to position their own product development. However, the information overload brought by the network development makes it getting difficult to obtain the accurate competitiveness information. Therefore, competitiveness analysis research to combine with the perceived helpfulness study needs urgent solution. Furthermore, deviations exist in the three common methods of perceived helpfulness research. Finally, the traditional information fusion analysis only analyzes the advantages and disadvantages of products in competitiveness analysis without taking account of the competitive environment.

Design/methodology/approach

This study puts forward a novel prediction model of perceived helpfulness in conjunction of unsupervised learning and sentiment analysis techniques, to conduct the comparison with pros and cons of congeneric products.

Findings

This paper adopts Wilcoxon test to demonstrate the significant rectification of our competitiveness analysis to the traditional methods. It is noted that the positive reviews of the products in this study impact more on product word of mouth and competitiveness than negative ones.

Originality/value

To sum up, the results of this study benefit businesses in locating their dynamic market position with competitors in practice and exploring new method for long-term development strategic planning.

Details

Data Technologies and Applications, vol. 57 no. 4
Type: Research Article
ISSN: 2514-9288

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Article
Publication date: 5 August 2024

Chengxi Yan, Yuchen Pan, Shaojian Li and Fuqian Zhang

National collaboration is an important topic for the development of digital humanities (DH). However, the collaboration patterns of DH have not been well studied in terms of…

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Abstract

Purpose

National collaboration is an important topic for the development of digital humanities (DH). However, the collaboration patterns of DH have not been well studied in terms of development stages and collaboration characteristics. This paper aims to reveal the typical patterns of country-level collaboration in the global environment of DH based on research capacity, network features and influence indicators.

Design/methodology/approach

We systematically designed a pipeline procedure based on the methods of bibliometrics and altmetrics to analyze global DH-related publications from two popular databases. The process includes the division of development stages, the identification of typical characteristics, the analysis of collaboration networks and the correlation test for different influences across countries.

Findings

The findings show that the collaboration in DH has certain characteristics and evolutionary patterns – with 2007 as the turning point that presents a gradual alteration from the strong competition of nation giants and the dominance of domestic collaboration to diversified international cooperation within regional alliances and a clear positive effect on national influence (both academic and social levels) by international collaboration. Some relevant suggestions are also put forward.

Originality/value

The study demonstrates not only the evidence of distinct patterns of country-level collaboration for DH during its evolutionary period as well as collaboration types and structures but also the positive effect of international collaboration on the enhancement of both academic influence and social attention. Moreover, the proposed analytical procedure provides insightful ideas around DH development from both the bibliometric and altmetric views, which can be an extensible framework for other scholarly collaboration research.

Details

Aslib Journal of Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2050-3806

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