Representations of Australia in South Korean online news: a qualitative and quantitative approach utilizing Leximancer and Korean keywords in context

Spry, Damien; Dwyer, Tim

doi:10.1007/s11135-016-0387-1

Cited by 10 publications

(9 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…From 2009, there is an increasing trend in the number of news articles. The rationale behind analyzing news before other data types is that news is generated from topics on social, corporate, government, and national issues in which the public may be interested [120]. Furthermore, it is generated by a third party, which means it is more likely to be objective than reports compiled by a firm [121,122].…”

Section: Datamentioning

confidence: 99%

“…This methodology is widely used in content analyses and has been employed in various studies [120,123]. It is based on the corpus linguistics observation [133].…”

Section: Leximancermentioning

confidence: 99%

“…Leximancer utilizes unsupervised learning, and generates information on simultaneous occurrences in two stages, based on semantic and relational methods, thereby ensuring methodological reliability. Leximancer ensures inter-coder reliability in category generation in comparison with manual coding methods, and also ensures reproducibility, with the same results being produced given the same data [120,123]. Furthermore, it reduces the time required for analysis, while achieving methodological rigor [149].…”

Section: Convenience and Usefulness Of Leximancer And Dictionmentioning

confidence: 99%

“…Leximancer is a representative methodology among the ever-evolving computer-assisted content analysis methods. While it may be criticized for being messy, it can contribute significantly to exploratory research, as a productive, open and truthful methodology [120,150].…”

Section: Convenience and Usefulness Of Leximancer And Dictionmentioning

confidence: 99%

See 3 more Smart Citations

Sustainable Supply Chain Based on News Articles and Sustainability Reports: Text Mining with Leximancer and DICTION

Kim

2017

Sustainability

View full text Add to dashboard Cite

Abstract:The purpose of this research is to explore sustainable supply chain management (SSCM) trends, and firms' strategic positioning and execution with regard to sustainability in the textile and apparel industry based on news articles and sustainability reports. Further analysis of the rhetoric in Chief executive officer (CEO) letters within sustainability reports is used to determine firms' resoluteness, positive entailments, sharing of values, perception of reality, and sustainability strategy and execution feasibility. Computer-based content analysis is used for this research: Leximancer is applied for text analysis, while dictionary-based text mining program DICTION and SPSS are used for rhetorical analysis. Overall, contents similar to the literature on environmental, social, and economic aspects of the triple bottom line (TBL) are observed, however, topics such as regulation, green incentives, and international standards are not readily observed. Furthmore, ethical issues, sustainable production, quality, and customer roles are emphasized in texts analyzed. The CEO letter analysis indicates that listed firms show relatively low realism and high commonality, while North American firms exhibit relatively high commonality, and Europe firms show relatively high realism. The results will serve as a baseline for providing academia guidelines in SSCM research, and provide an opportunity for businesses to complement their sustainability strategies and executions.

show abstract

Section: Datamentioning

confidence: 99%

“…This methodology is widely used in content analyses and has been employed in various studies [120,123]. It is based on the corpus linguistics observation [133].…”

Section: Leximancermentioning

confidence: 99%

Section: Convenience and Usefulness Of Leximancer And Dictionmentioning

confidence: 99%

Section: Convenience and Usefulness Of Leximancer And Dictionmentioning

confidence: 99%

See 2 more Smart Citations

Sustainable Supply Chain Based on News Articles and Sustainability Reports: Text Mining with Leximancer and DICTION

Kim

2017

Sustainability

View full text Add to dashboard Cite

show abstract

“…Exercisers have offered valuable information regarding their psychological commitment in a fitness club (Bodet, 2012), and their perceived service (Song, 2011) and environment (Kim, 2012) therein. However, traditional ways of information gathering and processing, such as in-person survey (Yan, Cardinal, & Acock, 2015), in-depth interview (Jones, 2011; Spry & Dwyer, 2017) and manual coding (Maguire, 2008; Smith, 2016), have been costly in terms of time, money and reliability. Therefore, developing, validating and implementing alternative ways of efficiently analyzing fitness club service quality are of critical significance.…”

Section: Introductionmentioning

confidence: 99%

Toward a better fitness club: Evidence from exerciser online rating and review using latent Dirichlet allocation and support vector machine

Jia

2018

International Journal of Market Research

View full text Add to dashboard Cite

Fitness clubs have never ceased searching for quality improvement opportunities to better serve their exercisers, whereas exercisers have been posting online ratings and reviews regarding fitness clubs. Studied together, the quantitative rating and qualitative review can provide a comprehensive depiction of exercisers’ perception of fitness clubs. However, the typological and dimensional discrepancies of online rating and review have hindered the joint study of the two data sets to fully exploit their business value. To this end, this study bridges the gap by examined 53,979 pairs of exerciser online rating and review from 100 fitness clubs in Shanghai, China. Using latent Dirichlet allocation (LDA) based text mining, we identified the 17 major topics on which the exercisers were writing. A support vector machine (SVM) classifier was then employed to establish the rating-review relations, with an accuracy rate of up to 86%. Finally, the relative impact of each topic on exerciser satisfaction was computed and compared by introducing virtual reviews. The significance of this study is that it systematically creates a standardized protocol of mining and correlating the massive structured/quantitative and unstructured/qualitative data available online, which is readily transferable to the other service and product sectors.

show abstract

Constants in context: an exploration of conciliar and post-conciliar documents on the Catholic school

2019

View full text Add to dashboard Cite

Representations of Australia in South Korean online news: a qualitative and quantitative approach utilizing Leximancer and Korean keywords in context

Cited by 10 publications

References 26 publications

Sustainable Supply Chain Based on News Articles and Sustainability Reports: Text Mining with Leximancer and DICTION

Sustainable Supply Chain Based on News Articles and Sustainability Reports: Text Mining with Leximancer and DICTION

Toward a better fitness club: Evidence from exerciser online rating and review using latent Dirichlet allocation and support vector machine

Constants in context: an exploration of conciliar and post-conciliar documents on the Catholic school

Contact Info

Product

Resources

About