Harnessing social media to understand tourist mobility: the role of information technology and big data

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jinyan Chen ◽  
Susanne Becken ◽  
Bela Stantic
Keyword(s):  
Social Media ◽  
Literature Review ◽  
Current Trend ◽  
Social Media Data ◽  
Content Type ◽  
Use Of Data ◽  
Social Media Platforms ◽  
The City ◽  
Media Data

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.

scholarly journals Success in an Online Giving Day: The Role of Social Media in Fundraising

2019 ◽  
Vol 49 (1) ◽  
pp. 74-92 ◽  
Author(s):  
Abhishek Bhati ◽  
Diarmuid McDonnell
Keyword(s):  
Social Media ◽  
Organizational Factors ◽  
Network Size ◽  
Audience Engagement ◽  
Social Media Data ◽  
Size Number ◽  
Social Media Platforms ◽  
The Relationship ◽  
Media Data

Social media platforms offer nonprofits considerable potential for crafting, supporting, and executing successful fundraising campaigns. How impactful are attempts by these organizations to utilize social media to support fundraising activities associated with online Giving Days? We address this question by testing a number of hypotheses of the effectiveness of using Facebook for fundraising purposes by all 704 nonprofits participating in Omaha Gives 2015. Using linked administrative and social media data, we find that fundraising success—as measured by the number of donors and value of donations—is positively associated with a nonprofit’s Facebook network size (number of likes), activity (number of posts), and audience engagement (number of shares), as well as net effects of organizational factors including budget size, age, and program service area. These results provide important new empirical insights into the relationship between social media utilization and fundraising success of nonprofits.

scholarly journals How social media reshapes action on distant customers: some empirical evidence

2017 ◽  
Vol 30 (4) ◽  
pp. 777-794 ◽  
Author(s):  
Deborah Agostino ◽  
Yulia Sidorova
Keyword(s):  
Social Media ◽  
Joint Control ◽  
Control Activity ◽  
Social Media Data ◽  
Content Type ◽  
Corporate Website ◽  
Social Media Platforms ◽  
The One ◽  
Centres Of Calculation ◽  
Media Data

Purpose The purpose of this paper is to investigate how centres of calculation, now emerging in connection with social media, impact on the process of acting on distant customers. Specifically, the authors are interested in exploring how the distance between the organization and its customer is affected and how knowledge is accumulated within this centre. Design/methodology/approach A case study in an Italian telecommunication company was conducted over a time horizon of two years, analysing data sources in the form of interviews, documents and reports, corporate website, social media platforms and participants’ observations. With the adoption of social media, the company configured a new centre of calculation, called monitoring room, in the attempt to accumulate knowledge about its customers. The authors unpacked the activity of the centre of calculation discussing its ability to perform action upon a distant periphery and the process of knowledge accumulation inside the centre itself. Findings The results highlight the implication of social media for “action at a distance”. On the one hand, social media blurs the distinction between the centre and a periphery giving rise to a de-centring, and stimulating a joint control activity between the customer and the organization. On the other hand, social media was found vulnerable in providing a unique knowledge about customers: accumulation cycles that exploit social media data can be replicated by users with skills in data analytics and the knowledge they provide might conflict with knowledge provided by traditional data. Originality/value The authors contribute to an emergent stream of literature that is investigating accounting implications derived from social media, by underlying the controversial effects connected with centres of calculation enacted by social media data. The authors suggest that, while social media data provide the organization with huge amount of information real time, at the same time, it contributes to de-centring allowing customers and external actors to act upon the organization, rather than improving knowledge inside the centre.

scholarly journals Launching Revolution: Social Media and the Egyptian Uprising’s First Movers

2018 ◽  
Vol 50 (3) ◽  
pp. 1025-1045 ◽  
Author(s):  
Killian Clarke ◽  
Korhan Kocak
Keyword(s):  
Social Media ◽  
The Internet ◽  
Social Media Data ◽  
Quantitative Evidence ◽  
Qualitative And Quantitative ◽  
Social Media Platforms ◽  
The Arab Spring ◽  
Media Data ◽  
First Mover

AbstractDrawing on evidence from the 2011 Egyptian uprising, this article demonstrates how the use of two social media platforms – Facebook and Twitter – contributed to a discrete mobilizational outcome: the staging of a successful first protest in a revolutionary cascade, referred to here as ‘first-mover mobilization’. Specifically, it argues that these two platforms facilitated the staging of a large, nationwide and seemingly leaderless protest on 25 January 2011, which signaled to hesitant but sympathetic Egyptians that a revolution might be in the making. It draws on qualitative and quantitative evidence, including interviews, social media data and surveys, to analyze three mechanisms that linked these platforms to the success of the January 25 protest: (1) protester recruitment, (2) protest planning and coordination, and (3) live updating about protest logistics. The article not only contributes to debates about the role of the Internet in the Arab Spring and other recent waves of mobilization, but also demonstrates how scholarship on the Internet in politics might move toward making more discrete, empirically grounded causal claims.

scholarly journals How Social Media Impacts Brand Value: The Mediating Role of Customer Satisfaction

2020 ◽  
Vol 13 (1) ◽  
pp. 82-96
Author(s):  
Anatoli Colicev ◽  
Pete O’Connor
Keyword(s):  
Social Media ◽  
Customer Satisfaction ◽  
User Generated Content ◽  
Social Media Marketing ◽  
Brand Value ◽  
Social Media Data ◽  
Mediating Role ◽  
Social Media Platforms ◽  
Media Data

The growing popularity of social media platforms has increased brand investments in social media marketing. However, it is not clear whether and how social media marketing leads to the creation of value for consumers and brands; therefore, we investigate how marketer and user-generated content on social media affects consumer and brand metrics. Based on the marketing productivity chain, we propose that customer satisfaction, a leading consumer metric, mediates the link between social media content and brand value. To test such assertions, we use a sample of 87 brands from 17 industries and collect a unique dataset that combines social media data from Facebook, Twitter, and YouTube with customer satisfaction, brand value, and advertising expenses. We find that user-generated content has a stronger effect on customer satisfaction than marketer-generated content. We also find that YouTube is the most effective platform for user generated content. Interestingly, we find that the effects of marketer-generated content depend on the brand’s corporate reputation. In other words, more reputable brands can leverage their marketer-generated content more effectively.

A framework for understanding citizens’ political participation in social media

2019 ◽  
Vol 33 (4) ◽  
pp. 1053-1075
Author(s):  
Vidushi Pandey ◽  
Sumeet Gupta ◽  
Manojit Chattopadhyay
Keyword(s):  
Social Media ◽  
Political Participation ◽  
Text Classification ◽  
Consumer Participation ◽  
Classification Algorithms ◽  
Social Media Data ◽  
Content Type ◽  
Social Media Platforms ◽  
Use Of Social Media ◽  
Media Data

Purpose The purpose of this paper is to explore how the use of social media by citizens has impacted the traditional conceptualization and operationalization of political participation in the society. Design/methodology/approach This study is based on Teorell et al.’s (2007) classification of political participation which is modified to suit the current context of social media. The authors classified 15,460 tweets along three parameters suggested in the framework with help of supervised text classification algorithms. Findings The analysis reveals that Activism is the most prominent form of political participation undertaken by people on Twitter. Other activities that were undertaken include Formal Political participation and Consumer participation. The analysis also reveals that identity of participant does not play a classifying role as expected from the theoretical framework. It was found that the social media as a platform facilitates new forms of participation which are not feasible offline. Research limitations/implications The current work considers only the microblogging platform of Twitter as the data source. For a more comprehensive insight, analysis of other social media platforms is also required. Originality/value To the best of the authors’ knowledge, this is one of the few analyses where such a large database covering multiple social media events has been created and analysed using supervised text classification algorithms. A large proportion of previous studies on social media have been based on case study and have limited analysis to only a particular event on social media. Although there exist a few works that have studied a vast and varied collection of social media data (Gaby and Caren, 2012; Shirazi, 2013; Rane and Salem, 2012), such efforts are few in number. This study aims to add to that stream of work where a wider and more generalized set of social media data is studied.

scholarly journals Measuring Americans’ Comfort With Research Uses of Their Social Media Data

2021 ◽  
Vol 7 (3) ◽  
pp. 205630512110338
Author(s):  
Sarah Gilbert ◽  
Jessica Vitak ◽  
Katie Shilton
Keyword(s):  
Social Media ◽  
Data Collection ◽  
Data Use ◽  
Data Types ◽  
Sensitive Data ◽  
Social Media Data ◽  
Content Type ◽  
Social Media Platforms ◽  
Diverse Data ◽  
Media Data

Research using online datasets from social media platforms continues to grow in prominence, but recent research suggests that platform users are sometimes uncomfortable with the ways their posts and content are used in research studies. While previous research has suggested that a variety of contextual variables may influence this discomfort, such factors have yet to be isolated and compared. In this article, we present results from a factorial vignette survey of American Facebook users. Findings reveal that researcher domain, content type, purpose of data use, and awareness of data collection all impact respondents’ comfort—measured via judgments of acceptability and concern—with diverse data uses. We provide guidance to researchers and ethics review boards about the ways that user reactions to research uses of their data can serve as a cue for identifying sensitive data types and uses.

scholarly journals Embed2Detect: temporally clustered embedded words for event detection in social media

2021 ◽  
Author(s):  
Hansi Hettiarachchi ◽  
Mariam Adedoyin-Olowe ◽  
Jagdev Bhogal ◽  
Mohamed Medhat Gaber
Keyword(s):  
Social Media ◽  
Event Detection ◽  
High Volume ◽  
Detection Methods ◽  
Word Embeddings ◽  
Agglomerative Clustering ◽  
Data Set ◽  
Social Media Data ◽  
Social Media Platforms ◽  
Media Data

AbstractSocial media is becoming a primary medium to discuss what is happening around the world. Therefore, the data generated by social media platforms contain rich information which describes the ongoing events. Further, the timeliness associated with these data is capable of facilitating immediate insights. However, considering the dynamic nature and high volume of data production in social media data streams, it is impractical to filter the events manually and therefore, automated event detection mechanisms are invaluable to the community. Apart from a few notable exceptions, most previous research on automated event detection have focused only on statistical and syntactical features in data and lacked the involvement of underlying semantics which are important for effective information retrieval from text since they represent the connections between words and their meanings. In this paper, we propose a novel method termed Embed2Detect for event detection in social media by combining the characteristics in word embeddings and hierarchical agglomerative clustering. The adoption of word embeddings gives Embed2Detect the capability to incorporate powerful semantical features into event detection and overcome a major limitation inherent in previous approaches. We experimented our method on two recent real social media data sets which represent the sports and political domain and also compared the results to several state-of-the-art methods. The obtained results show that Embed2Detect is capable of effective and efficient event detection and it outperforms the recent event detection methods. For the sports data set, Embed2Detect achieved 27% higher F-measure than the best-performed baseline and for the political data set, it was an increase of 29%.

How to build employees' relationship capital through different enterprise social media platform use: the moderating role of innovation culture

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Liang Ma ◽  
Xin Zhang ◽  
Gaoshan Wang ◽  
Ge Zhang
Keyword(s):  
Social Media ◽  
Information Exchange ◽  
Content Type ◽  
Enterprise Social Media ◽  
Work Related ◽  
Innovation Culture ◽  
Social Media Platforms ◽  
Relationship Capital ◽  
Moderating Role

PurposeThe purpose of the present study is to build a research model to study how the use of different enterprise social media platforms affects employees' relationship capital, and the moderating role of innovation culture is also examined.Design/methodology/approachStructural equation modeling was performed to test the research model and hypotheses. Surveys were conducted in an electronic commerce company in China that uses different social media platforms, generating 301 valid responses for analysis.FindingsFirst, private social media used for work-related purposes can contribute to employees' relationship capital, and public social media QQ used for work-related purposes can contribute to employees' communication quality. WeChat used for social-related purposes has a positive effect on employees' information exchange. Second, innovation culture acts as a positive moderator between work-related media use and employees' information exchange, while innovation culture acts as a negative moderator between social-related WeChat use and employees' information exchange. Third, innovation culture acts as a positive moderator between work-related QQ use and employees' trust, while innovation culture acts as a negative moderator between social-related QQ use and employees' trust.Originality/valueFirst, this paper contributes to the information system (IS) social media literature by studying the effect of the use of different enterprise social media platforms used for different purposes on employees' relationship capital. Second, the authors contribute to relationship capital theory by clarifying that use of public and private social media platforms for social- and work-related purposes is an important driver of the formation of employees' relational capital. Third, the present study also contributes to enterprise social media literature by confirming that innovation culture acts as a different moderator between use of different enterprise social media platforms and employees' relationship capital.

Google Plus as a Contentious Field of Revolutionary Identity

2021 ◽  
Vol 20 (3) ◽  
pp. 402-416
Author(s):  
Amirhossein Teimouri
Keyword(s):  
Social Media ◽  
Iranian Revolution ◽  
Social Media Data ◽  
Social Media Platforms ◽  
New Generation ◽  
Media Data

Abstract Social media platforms have been increasingly reinvigorating extreme movements, especially rightist movements. Utilizing unique Google Plus data, the author shows the rise and fall of the 2015 rightist anti-Nuclear Deal movement in Iran. He argues that the Google Plus platform in 2015 provided the new generation of revolutionary Islamist rightist activists with a contentious space of mobilization, enabling them to develop a new revolutionary rightist identity. This revolutionary identity and its corresponding language and discourse did not fully unfold in Iranian mainstream rightist media, even though rightist groups, compared to liberal groups, are not censored and repressed. The new generation of rightist activists perceived the Nuclear Deal as an existential threat to revolutionary principles of the country, and thus played out their outrage and identity anxieties on Google Plus. The author contends that this online outrage, due to the activists’ identity bond with the regime and the 1979 Iranian Revolution, however, did not translate into any massive offline mobilization against the Nuclear Deal. He also discusses the methodological implications of using social media data, especially the discontinuation of Google Plus.

Destination image through social media analytics and survey method

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Michael S. Lin ◽  
Yun Liang ◽  
Joanne X. Xue ◽  
Bing Pan ◽  
Ashley Schroeder
Keyword(s):  
Social Media ◽  
Survey Data ◽  
Destination Image ◽  
Social Media Analytics ◽  
Tourism Destination ◽  
Social Media Data ◽  
Content Type ◽  
Holistic Understanding ◽  
Intercept Survey ◽  
Media Data

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.

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