Bibliometrics, Using Text Mining to Review Twitter Usage in Tourism



Social media platforms are becoming ubiquitous in the tourism industry around the world. Travelers are using social media to write reviews, plan travel, connect with others and communicate with providers. Likewise, airlines, hotels, restaurants and tour companies, are using social media to market and promote their products, communicate with their clients and as a tactic of crisis communications. These are just a few examples. As a result of this activity academics are more and more studying the impact of social media on tourism. In their paper “Twitter Usage in Tourism: Literature Review” Business Systems Research, Vol. 10 No. 1, pp. 102-119 Curlin, T., Jakovic,B., Miloloza I. (2019) use text mining to perform a bibliometric analysis to identify significant authors, journals and institutions engaged in the research-oriented  utilization of Twitter in tourism and to extract and identify the words, phrases, topics and themes in this research.

After completing a systematic literature review using the phrase Twitter and Touris* and then eliminating papers not directly related to the research topic the authors compiled a list of 46 papers. They then used WordStat 8.0.9 to perform text mining on the abstracts of all the papers to extract words and phrases. Through the use of link analysis and the software’s proximity plot feature they identified the proximity between words and phrases and performed cluster analysis to identify common themes.

The cluster analysis identified seven topics based on the phrases extracted from the papers related to Twitter and tourism. Among their conclusions, the authors stated that, “the cluster analysis singled out the trends, methods and gaps in the literature. It specified six topics where an assorted number of sources confirmed the relationship of Twitter posts and tourist’s decision making, hotel branding, e-WoM and booking intentions so hotels and tourist destinations can create business and marketing strategies and more distinguished and personalized supply. Personalized supply is singled out as a critical factor in gaining competitive advantage and marketing spread.”

The paper shows the value of text analytics and text mining in performing bibliometric research. If you would like to read more about bibliometrics and scientometrics with Wordstat and QDA Miner you can access our white paper. You can read the full paper highlighted in this Blog here