Projected Destination Image Online: Website Content Analysis of Pictures and Text

Govers, Robert; Go, Franciscus

doi:10.3727/1098305054517327

Cited by 243 publications

(151 citation statements)

References 4 publications

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“…Gallarza, Saura and (Choi et al, 2007;Govers & Go, 2005;Tang, Choi, Morrison, & Lehto, 2009;Tang et al, 2011), television travel shows (Hanefors & Mossberg, 2002;Pan et al, 2011), travel guides (van Gorp & Beneker, 2007, and newspapers (Stepcenkova, Chen, & Morrison, 2007;Xiao & Mair, 2006). However, none of the projected image studies was conducted from a Mainland Chinese perspective.…”

Section: Destination Imagementioning

confidence: 99%

Projected Images of Major Chinese Outbound Destinations

Hsu

Song

2012

Asia Pacific Journal of Tourism Research

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Section: Destination Imagementioning

confidence: 99%

Projected Images of Major Chinese Outbound Destinations

Hsu

Song

2012

Asia Pacific Journal of Tourism Research

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“…The attractive factors are examined for both their relative importance as well as various "importance clusters". As there are over 30 elements examined in this study, attractive elements were only examined based on word frequency, a method which has been frequently used in tourism evaluation texts to analyze tourist destination image perception [34,42,43]. The frequency of words represents a tourists' interests or focus.…”

Section: Keyword Prioritizationmentioning

confidence: 99%

Comparing Social Media Data and Survey Data in Assessing the Attractiveness of Beijing Olympic Forest Park

Wang

Liu

et al. 2018

Sustainability

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Abstract:Together with the emerging popularity of big data in numerous studies, increasing theoretical discussions of the challenges and limitations of such data sources exist. However, there is a clear research gap in the empirical comparison studies on different data sources. The goal of this paper is to use "attractiveness" as a medium to examine the similarity and differences of Social media data (SMD) and survey data in academic research, based on a case study of the Beijing Olympic Forest Park, in Beijing, China. SMD was extracted from two social media platforms and two surveys were conducted to assess the attractiveness of various locations and landscape elements. Data collection, keyword extraction and keyword prioritization were used and compared in the data gathering and analysis process. The findings revealed that SMD and survey data share many similarities. Both data sources confirm that natural ambience is more appreciated than cultural elements, particularly the naturalness of the park. Spaces of practical utility are more appreciated than facilities designed to have cultural meanings and iconic significance. Despite perceived similarities, this study concludes that SMD exhibits exaggerated and aggregated bias. This resulted from the intrinsic character of SMD as volunteered and unstructured data selected through an emotional process rather than from a rational synthesis. Exciting events were reported more often than daily experiences. Reflecting upon the strength and weakness of SMD and survey data, this study would recommend a combined landscape assessment process, which first utilizes SMD to build up an assessment framework, then applies conventional surveys for supplementary and detailed information. This would ultimately result in comprehensive understanding.

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“…Researchers have performed content analysis by measuring the frequency of certain images or text on a tourism website [33]. Other researchers have conducted web content analysis using a new mechanism evolved from previous studies [42].…”

Section: Content Analysismentioning

confidence: 99%

A Content Analysis for Website Usefulness Evaluation: Utilizing Text Mining Technique

Kwon¹,

Jeong²

2015

Journal of Internet Computing and Services

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With the increasing influence of online media, company websites have become important communication channels between companies and customers. Companies use their websites as a marketing tool for a variety of purposes, including enhancing their image and selling products or services. Many researchers have examined the criteria, methods, and tools for website evaluation, but most have focused on usability. Prior content analyses have focused not on text content but on website components, an approach likely to produce subjective evaluations. This study attempts to objectively evaluate company websites by utilizing text mining. We analyze the usefulness of company websites by presenting visualized outputs from a business perspective, allowing practitioners to easily understand the results of the website evaluation and use them in decision making. To demonstrate our method empirically, we selected a company with a number of affiliates in Korea and analyzed the text content of their websites to assess their usefulness using natural language processing and graphics packages in R. Practitioners can easily employ our objective evaluation method, and researchers can use it to gain a new perspective on website evaluation.

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Projected Destination Image Online: Website Content Analysis of Pictures and Text

Cited by 243 publications

References 4 publications

Projected Images of Major Chinese Outbound Destinations

Projected Images of Major Chinese Outbound Destinations

Comparing Social Media Data and Survey Data in Assessing the Attractiveness of Beijing Olympic Forest Park

A Content Analysis for Website Usefulness Evaluation: Utilizing Text Mining Technique

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