Knowledge Dissemination of Word-of-Mouth Research: Citation Analysis and Social Network Analysis

Lin, Tom M.Y.; Liao, Chun-Wei

doi:10.1515/libr.2008.022

Cited by 10 publications

(7 citation statements)

References 31 publications

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“…All of that involves mathematics. In this case, the methodology for expressing the birth of science is offer: As the order in which the terms appear (if there are in various means such as dictionaries); Study programs (academic facilities for organizing it); Scientific meetings or journals (as a means of accumulation and dissemination) or also the number of documents (as an evidence of growth) (Ben-David & Loewy, 2000;Gupta, 1997;Green, Johnson, & Neal, 2003;Lin & Liao, 2008;Zanotto, Vanz, & Stumpf, 2017;Nasution, 2019).…”

Section: Methodsmentioning

confidence: 99%

The birth of a science

Nasution

2020

Hist. sci. technol.

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Physics, biology, chemistry, for example, do not already only study programs in many universities but are at the forefront of the development of science, and that is science itself. The development of the basic foundation becomes the mother of science, such as mathematics, as a suspicion of the birth of new sciences. The interests related to the life and welfare of humans always invites the possibility of the birth of science in concepts, but mathematics confirms it. In certain cases, as an application, or it gives birth to answers in technology form, which is distorted according to the social demands of society. Every science has its methodology, which is based on the logic that helps to reason. A natural model is an approach to generating methods, as well as the principles that develop in artificial intelligence based on mathematics. This principle not only changes the way of perceiving data, but it also establishes new definitions of data, and changes statistics, optimization, and other fields. Each science also has implications for other sciences but also has applications that are also related to other sciences. Every science supports technology to improve social welfare. Historically, century by century, many new scientific fields were born, and it has evidence from the publication of scientific works to books as scientific standards. Then, the teaching curricula supported its initial dissemination and its development through research with evidence of scientific publications either through papers in proceedings of scientific meetings or articles in the journals. A study program about science in the related faculty is mandatory, and it is as the spearhead in further scientific and technological development. So everything starts and ends at one point, namely the birth of new science, as the birth of data science. This paper describes the birth of science by involving historical traces. The reflection of scientific development is starting from the foundation to become a scientific field, namely data science. It also illustrates the roadmap of a scientific indirectly.

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Section: Methodsmentioning

confidence: 99%

The birth of a science

Nasution

2020

Hist. sci. technol.

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“…Over time, studies have developed to understand the current status and course of all players of the scientific community. For example, there are studies that have used the social network analysis method on issues such as inter-journal relations, how information flow develops and the classification of journals (Leydesdorff, 2004(Leydesdorff, , 2007Biehl et al, 2006;Lin and Liao, 2008;Polites and Watson, 2009). Social network analysis measures were also used to visualize the disciplines of scientific journals (Leydesdorff, 2007).…”

Section: Lht 413mentioning

confidence: 99%

Social network analysis of mythology field

Akça

Akbulut

2021

LHT

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PurposeThe main purpose of the study is to detect, monitor the mythology field and make predictions of the development of it using social network analysis metrics. Mythology, which is the subject of many disciplines, is an area with extensive working potential. In addition to basic bibliometric indicators, the relationships of this field, which cannot be seen by other methods, were analyzed using measures such as centrality, between, eigenvector, modularity and silhouette coefficients.Design/methodology/approachIn this study, social network analysis of the field of mythology, which has an interdisciplinary structure, was made. Within the scope of the study, 28,370 publications were selected from the publications in the field of mythology in the Web of Science (WoS) citation database between 1900 and 2019 using the probability-based stratified sampling method (5%), and detailed analyzes were made on these publications. The aforementioned publications were analyzed in terms of publication and citation numbers, publication types, subject categories, keywords used, co-authorship, researchers with the highest number of publications, institutions and countries with the highest number of document co-citations.FindingsThe findings show that the field of mythology gathers around four main subjects (sociology, folklore, politics and anthropology). When interpreted in terms of centrality metrics in more detail, the symbiotic or complementary relationship between anthropology, folklore, politics, sociology and mythology can be easily observed.Originality/valueThe findings of this study are seen important for scientists, decision-makers and policymakers. In addition, the findings of the study can be used to create the curriculum of the field.

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“…One, much of the existing research on WOM has been undertaken in developed countries, resulting in calls for further studies on WOM in developing countries (e.g. Lin and Liao, 2008). Two, there is some evidence that culture may play a part in the impact of WOM (e.g.…”

Section: Main Studymentioning

confidence: 99%

“…Two, there is some evidence that culture may play a part in the impact of WOM (e.g. Lin and Liao, 2008;Money et al, 1998) and, as service firms become increasingly globally diversified, understanding the influence of cultural differences becomes more important (Swanson et al, 2011). To date, the few studies that have compared the relative influence of pWOM and eWOM in service consumption decision making, albeit only in the context of positive WOM (e.g.…”

Section: Main Studymentioning

confidence: 99%

Is negative eWOM more influential than negative pWOM?

Bachleda

Berrada-Fathi

2016

Journal of Service Theory and Practice

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Purpose – The purpose of this paper is to examine the influence of various sources of negative electronic word-of-mouth (eWOM) and negative personal word-of-mouth (pWOM) on trust in the Word-of-mouth (WOM), attitude toward the service provider and purchase intention. Design/methodology/approach – Data were gathered from 336 Moroccan workers who responded to an online survey. Findings – Results show that negative pWOM is more influential than negative eWOM in the form of written Facebook testimonials, written review site testimonials and written testimonials on a corporate website. However, there is a relative ranking of importance among eWOM sources, with review site testimonials found to be more influential than either Facebook or corporate website testimonials. Research limitations/implications – This work responds to a call for research on differences and similarities between pWOM and eWOM. The findings extend understanding of the relative influence of negative pWOM and negative eWOM. Practical implications – The results of this study provide guidance to service marketers in terms of strategies for deflecting negative WOM and allocating service recovery resources. Originality/value – This study is the first to compare the relative influence of negative pWOM and eWOM in service consumption.

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Knowledge Dissemination of Word-of-Mouth Research: Citation Analysis and Social Network Analysis

Cited by 10 publications

References 31 publications

The birth of a science

The birth of a science

Social network analysis of mythology field

Is negative eWOM more influential than negative pWOM?

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