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Article
Publication date: 17 November 2022

Sungwon Oh, Min Jae Park, Tae You Kim and Jiho Shin

This study aimed to present the methodology of the text data analysis to establish marketing strategies for fintech companies in a practical way. Specifically, the methodology was…

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Abstract

Purpose

This study aimed to present the methodology of the text data analysis to establish marketing strategies for fintech companies in a practical way. Specifically, the methodology was presented to convert customers' review data, which consisted of the text data (unstructured data), to the numerical data (structured data) by using a text mining algorithm “Global Vectors for Word Representation,” abbreviated as “GloVe”; additionally, the authors presented the methodology to deploy the numerical data for marketing strategies with eliminate-reduce-raise-create (ERRC) value factor analytics.

Design/methodology/approach

First, the authors defined the background, features and contents of fintech services based on a review of related literature review. Additionally, they examined business strategies, the importance of social media for fintech services and fintech technology trends based on the literature review. Next, they analyzed the similarity between fintech-related keywords, which represent the trends in fintech services, and the text data related to fintech corporations and their services posted on Facebook and Twitter, which are two of the most popular social media globally, during the period 2017–2019. The similarity was then quantified and categorized in terms of the representative global fintech companies and the status of each fintech service sector. Furthermore, the similarity was visualized, and value elements were rebuilt using ERRC strategy analytics.

Findings

This study is meaningful in that it quantifies the degree of similarity between customers' responses, experiences and expectations regarding the rapidly growing global fintech firms' services and trends in fintech services.

Originality/value

This study suggests a practical way to apply in business by providing a method for transforming unstructured text data into structured numerical data it is measurable. It is expected that this study can be used as the basis for exploring sustainable development strategies for the fintech industry.

Details

Management Decision, vol. 61 no. 1
Type: Research Article
ISSN: 0025-1747

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Article
Publication date: 9 May 2023

Magnus Osahon Igbinovia and Bolanle Clifford Ishola

Technological expansion and adoption in university libraries have precipitated cybercrimes and the need to equip library personnel with the required knowledge to combat this…

750

Abstract

Purpose

Technological expansion and adoption in university libraries have precipitated cybercrimes and the need to equip library personnel with the required knowledge to combat this menace. Consequently, this study aims to examine cyber security in university libraries and its implication for Library and Information Science education.

Design/methodology/approach

The study adopted descriptive research design, while questionnaire and interview were used to elicit data from library personnel and heads of library schools, respectively. A total of 134 responses were elicited through structured questionnaire (administered online due to the closure of universities) while six heads of library schools were interviewed, one from each of the six geopolitical zones in Nigeria.

Findings

The data from the questionnaire which were descriptively analysed revealed that the perceived knowledge of cyber security among the librarians was moderately low. Also, the university libraries were exposed to various cyber threats, with cyber security/guideline been one of the critical measures to combat cybercrime. Also, the result showed that librarians displayed high level of adherence to cyber ethics. However, the disposition of library management towards cyber security issues was revealed to be the main challenge to the deployment of cyber security in university libraries, follow by poor password management. Majority of the librarians possess basic knowledge of cyber security, though with serious interest to learn more about it. They were not taught cyber security in library school and they indicated enthusiasm to learn about it. The result of the interview with heads of library schools showed majority of these schools do not offer cyber security course due to dearth in skilled manpower.

Originality/value

The study presents cybercrime as a menace, if not tackled, would affect the university libraries’ sustainability as information institution, compromising their ability to deliver quality services.

Details

Digital Library Perspectives, vol. 39 no. 3
Type: Research Article
ISSN: 2059-5816

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Article
Publication date: 26 December 2024

Jiho Kim, Youngjun Jang, Wongyeom Seo and Hongchul Lee

Information filtering systems serve as robust tools in the ongoing difficulties associated with overwhelming volumes of data. With constant generation and accumulation of reviews…

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Abstract

Purpose

Information filtering systems serve as robust tools in the ongoing difficulties associated with overwhelming volumes of data. With constant generation and accumulation of reviews in online communities, the ability to distill and provide valuable insights to assist customers in their search for relevant information is of considerable significance. This study devised an effective review filtering system for a popular online physical experience review site.

Design/methodology/approach

This study entailed an investigation of a hybrid approach for a review filtering system augmented with various text mining-based operational variables to extract the linguistic signals of online reviews. Moreover, we devised three ensemble models based on multiple machine learning and deep learning algorithms to build a high-performance review filtering system.

Findings

The main findings confirm the effectiveness of using the derived operational variables when reviewing filtering systems. We found that the reviewer’s tendency and history macros, as well as the readability and sentiment of the reviews, contribute significantly to the filtering performance. Furthermore, the proposed three ensemble frameworks demonstrated good efficiency with an average accuracy of 89.39%.

Originality/value

This study provides a methodological blueprint for operationalizing variables in online reviews, covering both structured and unstructured datasets. Incorporating different variables enhances the efficiency of the algorithm and provides a more comprehensive understanding of user-generated content. Furthermore, the study affords a strategic perspective and integrated guidelines for developers seeking to create advanced review filtering systems.

Details

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

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