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Article
Publication date: 1 September 2021

Yuting Jiang, Shengli Deng, Hongxiu Li and Yong Liu

The purposes of this paper are to (1) explore how personality traits pertaining to the dominance influence steadiness compliance model manifest themselves in terms of user…

Abstract

Purpose

The purposes of this paper are to (1) explore how personality traits pertaining to the dominance influence steadiness compliance model manifest themselves in terms of user interaction behavior on social media and (2) examine whether social interaction data on social media platforms can predict user personality.

Design/methodology/approach

Social interaction data was collected from 198 users of Sina Weibo, a popular social media platform in China. Their personality traits were also measured via questionnaire. Machine learning techniques were applied to predict the personality traits based on the social interaction data.

Findings

The results demonstrated that the proposed classifiers had high prediction accuracy, indicating that our approach is reliable and can be used with social interaction data on social media platforms to predict user personality. “Reposting,” “being reposted,” “commenting” and “being commented on” were found to be the key interaction features that reflected Weibo users' personalities, whereas “liking” was not found to be a key feature.

Originality/value

The findings of this study are expected to enrich personality prediction research based on social media data and to provide insights into the potential of employing social media data for the purpose of personality prediction in the context of the Weibo social media platform in China.

Details

Aslib Journal of Information Management, vol. 73 no. 6
Type: Research Article
ISSN: 2050-3806

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Article
Publication date: 30 August 2021

Jinyan Chen, Susanne Becken and Bela Stantic

This paper aims to examine key parameters of scholarly context and geographic focus and provide an assessment of theoretical underpinnings of studies in the field of social

Abstract

Purpose

This paper aims to examine key parameters of scholarly context and geographic focus and provide an assessment of theoretical underpinnings of studies in the field of social media and visitor mobility. This review also summarised the characteristics of social media data, including how data are collected from different social media platforms and their advantages and limitations. The stocktake of research in this field was completed by examining technologies and applied methods that supported different research questions.

Design/methodology/approach

This literature review applied a mix of methods to conduct a literature review. This review analysed 82 journal articles on using social media to track visitors’ movements between 2014 and November 2020. The literature compared the different social media, discussed current applied theories, available technologies, analysed the current trend and provided advice for future directions.

Findings

This review provides a state-of-the-art assessment of the research to date on tourist mobility analysed using social media data. The diversity of scales (with a dominant focus on the city-scale), platforms and methods highlight that this field is emerging, but it also reflects the complexity of the tourism phenomenon. This review identified a lack of theory in this field, and it points to ongoing challenges in ensuring appropriate use of data (e.g. differentiating travellers from residents) and the ethics surrounding them.

Originality/value

The findings guide researchers, especially those with no computer science background, on the different types of approaches, data sources and methods available for tracking tourist mobility by harnessing social media. Depending on the particular research interest, different tools for processing and visualization are available.

Details

Tourism Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1660-5373

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Article
Publication date: 15 June 2021

Kathy R. Fitzpatrick and Paula L. Weissman

The aim of this study was to understand how public relations leaders view and use social media analytics (SMA) and the impact of SMA on the public relations function.

Abstract

Purpose

The aim of this study was to understand how public relations leaders view and use social media analytics (SMA) and the impact of SMA on the public relations function.

Design/methodology/approach

The research involved in-depth interviews with chief communication officers (CCOs) from leading multinational corporate brands.

Findings

The findings revealed that although CCOs perceive social media analytics as strategically important to the advancement of public relations, the use of social media data is slowed by challenges associated with building SMA capacity.

Theoretical and practical implications

The research extends public relations theory on public relations as a strategic management function and provides practical insights for building SMA capabilities.

Originality/value

The study is among the first to provide empirical evidence of how companies are using social media analytics to enhance public relations efforts.

Details

Journal of Communication Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1363-254X

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Article
Publication date: 10 June 2021

Michael S. Lin, Yun Liang, Joanne X. Xue, Bing Pan and Ashley Schroeder

Recent tourism research has adopted social media analytics (SMA) to examine tourism destination image (TDI) and gain timely insights for marketing purposes. Comparing the…

Abstract

Purpose

Recent tourism research has adopted social media analytics (SMA) to examine tourism destination image (TDI) and gain timely insights for marketing purposes. Comparing the methodologies of SMA and intercept surveys would provide a more in-depth understanding of both methodologies and a more holistic understanding of TDI than each method on their own. This study aims to investigate the unique merits and biases of SMA and a traditional visitor intercept survey.

Design/methodology/approach

This study collected and compared data for the same tourism destination from two sources: responses from a visitor intercept survey (n = 1,336) and Flickr social media photos and metadata (n = 11,775). Content analysis, machine learning and text analysis techniques were used to analyze and compare the destination image represented from both methods.

Findings

The results indicated that the survey data and social media data shared major similarities in the identified key image phrases. Social media data revealed more diverse and more specific aspects of the destination, whereas survey data provided more insights in specific local landmarks. Survey data also included additional subjective judgment and attachment towards the destination. Together, the data suggested that social media data should serve as an additional and complementary source of information to traditional survey data.

Originality/value

This study fills a research gap by comparing two methodologies in obtaining TDI: SMA and a traditional visitor intercept survey. Furthermore, within SMA, photo and metadata are compared to offer additional awareness of social media data’s underlying complexity. The results showed the limitations of text-based image questions in surveys. The findings provide meaningful insights for tourism marketers by having a more holistic understanding of TDI through multiple data sources.

Details

International Journal of Contemporary Hospitality Management, vol. 33 no. 6
Type: Research Article
ISSN: 0959-6119

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Book part
Publication date: 30 October 2020

Vanessa Ratten

There has been a digital transformation of the sport industry that has resulted in an increase in the number of startups. Technological innovations derived from big data

Abstract

There has been a digital transformation of the sport industry that has resulted in an increase in the number of startups. Technological innovations derived from big data and social media have altered the way entrepreneurship is embedded in a sport context. This has influenced more technologically enabled sport startups that are driving change in the global economy. This chapter discusses the role of digitalization in changing existing business models and fostering a more entrepreneurial ecosystem. This includes focusing on technological innovations such as the impact of cloud computing and other data changes.

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Book part
Publication date: 12 December 2017

Wasim Ahmed, Peter A. Bath and Gianluca Demartini

This chapter provides an overview of the specific legal, ethical, and privacy issues that can arise when conducting research using Twitter data. Existing literature is…

Abstract

This chapter provides an overview of the specific legal, ethical, and privacy issues that can arise when conducting research using Twitter data. Existing literature is reviewed to inform those who may be undertaking social media research. We also present a number of industry and academic case studies in order to highlight the challenges that may arise in research projects using social media data. Finally, the chapter provides an overview of the process that was followed to gain ethics approval for a Ph.D. project using Twitter as a primary source of data. By outlining a number of Twitter-specific research case studies, the chapter will be a valuable resource to those considering the ethical implications of their own research projects utilizing social media data. Moreover, the chapter outlines existing work looking at the ethical practicalities of social media data and relates their applicability to researching Twitter.

Details

The Ethics of Online Research
Type: Book
ISBN: 978-1-78714-486-6

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Book part
Publication date: 12 December 2017

Leanne Townsend and Claire Wallace

Over the past decade, the number of people engaging with social media has grown rapidly. This means that social media platforms such as Twitter and Facebook are…

Abstract

Over the past decade, the number of people engaging with social media has grown rapidly. This means that social media platforms such as Twitter and Facebook are potentially good sources of rich, naturally occurring data. As a result, a growing number of researchers are utilizing these platforms for the collection of data on any number of topics. To date, no consistent approach to the ethics of using social media data has been provided to researchers in this sphere. This chapter presents research that has developed an ethics framework for the use of researchers working with social media data. The chapter also presents the framework itself and guidance on how to use the framework when conducting social media research. A full report can be accessed on: http://www.abdn.ac.uk/socsci/research/new-europe-centre/information-societies-projects-225.php

Details

The Ethics of Online Research
Type: Book
ISBN: 978-1-78714-486-6

Keywords

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Book part
Publication date: 12 December 2017

Libby Bishop and Daniel Gray

The focus of this chapter is the intersection of social media, publication, data sharing, and research ethics. By now there is an extensive literature on the use of social

Abstract

The focus of this chapter is the intersection of social media, publication, data sharing, and research ethics. By now there is an extensive literature on the use of social media in research. There is also excellent work on challenges of postpublication sharing of social media, primarily focused on legal restrictions, technical infrastructure, and documentation. This chapter attempts to build upon and extend this work by using cases to deepen the analysis of ethical issues arising from publishing and sharing social media data. Publishing will refer to the presentation of data extracts, aggregations, or summaries, while sharing refers to the practice of making the underlying data available postpublication for others to use. It will look at the ethical questions that arise both for researchers (or others) sharing data, and those who are using data that has been made available by others, emphasizing the inherently relational nature of data sharing. The ethical challenges researchers face when considering sharing user-generated content collected from social media platforms are the focus of the cases. The chapter begins by summarizing the general principles of research ethics, then identifies the specific ethical challenges from sharing social media data and positions these challenges in the context of these general principles. These challenges are then analyzed in more detail with cases from research projects that drew upon several different genres of social media. The chapter concludes with some recommendations for practical guidance and considers the future of ethical practice in sharing social media data.

Details

The Ethics of Online Research
Type: Book
ISBN: 978-1-78714-486-6

Keywords

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Book part
Publication date: 12 December 2017

Steven Ginnis

Social media provides researchers with easy access to rich, real-time data that offers insight into both public opinion and the role of social media in public life…

Abstract

Social media provides researchers with easy access to rich, real-time data that offers insight into both public opinion and the role of social media in public life. However, to date, good practice in analyzing social media has been led by what is technically possible and commercially viable. This chapter seeks to reverse that trend and is the result of a year-long study ‘Wisdom of the Crowd’ by Ipsos MORI, Demos, the University of Sussex and CASM Consulting to examine the ethical landscape surrounding aggregated social media research. Based on a review of the legal and market research regulatory landscape in the UK and a program of primary research with experts, members of the public and social media users, this chapter provides a series of constructive and practical recommendations on how to improve ethical standards in this field. Drawing on the context of public ethics, the recommendations provide advice to researchers, regulators, and social media organizations on how they can help to restore trust in social media research and better safeguard social media users.

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Book part
Publication date: 7 August 2019

Cristina Alaimo and Jannis Kallinikos

Social media stage online patterns of social interaction that differ remarkably from ordinary forms of acting, talking and relating. To unravel these differences, we…

Abstract

Social media stage online patterns of social interaction that differ remarkably from ordinary forms of acting, talking and relating. To unravel these differences, we review the literature on micro-sociology and social psychology and derive a shorthand version of socially-embedded forms of interaction. We use that version as a yardstick for reconstructing and assessing the patterns of sociality social media promote. Our analysis shows that social media platforms stage highly stylized forms of social interaction such as liking, following, tagging, etc. that essentially serve the purpose of generating a calculable and machine-readable data footprint out of user platform participation. This online stylization of social interaction and the data it procures are, however, only the first steps of what we call the infrastructuring of social media. Social media use the data footprint that results from the stylization of social interaction to derive larger (and commercially relevant) social entities such as audiences, networks and groups that are constantly fed back to individuals and groups of users as personalized recommendations of one form or another. Social media infrastructure sociality as they provide the backstage operations and technological facilities out of which new habits and modes of social relatedness emerge and diffuse across the social fabric.

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