Does ostracism impede Chinese tourist self-disclosure on WeChat? The perspective of social anxiety and self-construal

Cao, Xingping; Luo, Zeyuan; Qiu, Junlin; Liu, Yan

doi:10.1016/j.jhtm.2022.02.013

Cited by 21 publications

(5 citation statements)

References 85 publications

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“…Lastly, in relation to the studies on self-construal theory (Markus and Kitayama, 1991), this paper suggests that individuals’ self-construal orientation can shift due to the external environmental factor, namely, perceived threat. Past studies have been mainly focused on the effect of self-construal orientation as an individuals’ dispositional characteristic (Brockner et al , 2005; Cao et al , 2022) and/or as a situationally manipulated orientation (Sharifi and Spassova, 2020) on their decisions and behaviors. Extant literature has also investigated the role of self-construal in explaining the cross-cultural differences in service perception (Wang and Mattila, 2011) or online review generation (Tsiotsou, 2019).…”

Section: Discussionmentioning

confidence: 99%

The effect of perceived threat on online service reviews

Kim

Lee²

2022

JSM

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Purpose The ongoing impact of COVID-19 and the subsequent perception of threat have shifted consumer perceptions and evaluations of service experiences. This paper aims to investigate how customers’ service evaluation is shared as customer reviews following the pandemic and the heightened perception of threat. In doing so, this research particularly investigates the shifts in the textual contents of online reviews. Design/methodology/approach This study used the textual contents in the online reviews posted on Hotels.com for 1,497 hotels in New York City for empirical analysis. In total, 109,190 observations were used for the analysis. Findings By analyzing actual online review data from an online review platform for hotel services, this study finds that the text reviews generated after the pandemic outbreak tend to contain words with stronger negative emotions. In terms of the pronoun choice, this study further finds that the use of “I” increases while the use of “we” decreases. Originality/value This research adds to the existing literature on service evaluation and online customer reviews by showing that there are shifts in the expressions used to communicate service evaluation through online text reviews, including the degree of emotionality and pronoun usage. Because potential customers are likely to rely on online reviews for their own decisions, the findings suggest that it is important for practitioners to be aware of such shifts and respond accordingly.

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Section: Discussionmentioning

confidence: 99%

The effect of perceived threat on online service reviews

Kim

Lee²

2022

JSM

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“…Combining the development stage of WeChat marketing and the current situation and shortcomings of scenic spot WeChat marketing performance evaluation, based on the AISAS theory, the WeChat end scenic spot regional index marketing performance evaluation system has been established [12]. The literature defines the concepts of WeChat marketing and WeChat scenic spot marketing, and proposes that the WeChat scenic spot marketing involved in this paper is based on WeChat official account marketing [13]. Based on the AISAS theory and WeChat marketing measures, WeChat marketing performance evaluation indicators are selected.…”

Section: Related Workmentioning

confidence: 99%

Application of Internet big data analysis technology based on deep learning in tourism marketing performance evaluation

Yin

2023

Preprint

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Marketing through the network is the basic marketing method in the information age. It has certain marketing value, and its position has gradually become stable. It has become the mainstream marketing method, especially praised by the tourism industry, which has injected fresh blood into this field. As the development of tourism market is dynamic, businesses will consider the needs of tourists when paying attention to its development process, so as to design performance evaluation criteria for tourism marketing. Under this research background, this paper has completed the Internet marketing performance evaluation system for the tourism market by introducing big data analysis technology and in-depth learning technology. This system can effectively evaluate the actual development of the tourism industry, and the system design comprehensively considers the 360-degree performance appraisal and balanced integral models. Based on the actual tourism data of a certain place, this study summarizes some additional evaluation indicators, thus improving the evaluation model and laying the foundation for the introduction of data and model construction process of AHP. According to the principle of maximum membership, the following experimental results can be obtained: due to the poor performance evaluation results of a scenic spot, its membership is the largest. It can be seen from this that the Internet marketing performance evaluation system for the tourism market has practical application value and can effectively analyze market performance. This paper improves the performance evaluation system by introducing in-depth learning and big data analysis technology into the tourism market performance analysis.

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“…Researchers have studied self-disclosure in social networks, which is mostly done unconsciously [28,29]. Existing research on self-disclosure behavior primarily utilizes the questionnaire survey for privacy information in specifc felds.…”

Section: Introductionmentioning

confidence: 99%

An Automatic Privacy-Aware Framework for Text Data in Online Social Network Based on a Multi-Deep Learning Model

Liu,

Sun,

et al. 2023

International Journal of Intelligent Systems

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With the increasing severity of user privacy leaks in online social networks (OSNs), existing privacy protection technologies have difficulty meeting the diverse privacy protection needs of users. Therefore, privacy-aware (PA) for the text data that users post on OSNs has become a current research focus. However, most existing PA algorithms for OSN users only provide the types of privacy disclosures rather than the specific locations of disclosures. Furthermore, although named entity recognition (NER) technology can extract specific locations of privacy text, it has poor recognition performance for nested and interest privacy. To address these issues, this paper proposes a PA framework based on the extraction of OSN privacy information content. The framework can automatically perceive the privacy information shared by users in OSNs and accurately locate which parts of the text are leaking sensitive information. Firstly, we combine the roformerBERT model, BI_LSTM model, and global_pointer algorithm to construct a direct privacy entity recognition (DPER) model for solving the specific privacy location recognition and entity nesting problems. Secondly, we use the roformerBERT model and UniLM framework to construct an interest privacy inference (IPI) model for interest recognition and to generate interpretable text that supports this interest. Finally, we constructed a dataset of 13,000 privacy-containing texts for experimentation. Experimental results show that the overall accuracy of the DPER model can reach 91.80%, while that of the IPI model can reach 98.3%. Simultaneously, we compare the proposed model with recent methods. The analysis of the results indicates that the proposed model exhibits better performance than previous methods.

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Does ostracism impede Chinese tourist self-disclosure on WeChat? The perspective of social anxiety and self-construal

Cited by 21 publications

References 85 publications

The effect of perceived threat on online service reviews

The effect of perceived threat on online service reviews

Application of Internet big data analysis technology based on deep learning in tourism marketing performance evaluation

An Automatic Privacy-Aware Framework for Text Data in Online Social Network Based on a Multi-Deep Learning Model

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