A Sentiment Analysis and Role of Twitter for Health Communications

2022 ◽  
pp. 188-205
Author(s):  
Erkan Çiçek ◽  
Uğur Gündüz
Keyword(s):  
Social Media ◽  
Crisis Management ◽  
Semantic Analysis ◽  
Social Media Data ◽  
Global Pandemic ◽  
The Difference ◽  
Textual Content ◽  
The Impact ◽  
Media Data

Social media has been in our lives so much lately that it is an undeniable fact that global pandemics, which constitute an important part of our lives, are also affected by these networks and that they exist in these networks and share the users. The purpose of making this hashtag analysis is to reveal the difference in discourse and language while analyzing Twitter data and to evaluate the effects of a global pandemic crisis on language, message, and crisis management with social media data. This form of analysis is typically completed through amassing textual content data then investigating the “sentiment” conveyed. Within the scope of the study, 11,300 Twitter messages posted with the #stayhome hashtag between 30 May 2020 and 6 June 2020 were examined. The impact and reliability of social media in disaster management could be questioned by carrying out a content analysis based totally on the semantic analysis of the messages given on the Twitter posts with the phrases and frequencies used.

scholarly journals Stayhome Hashtag: Sentiment Analysis on Twitter During the Covid-19 Pandemic

2020 ◽  
Vol 16 (34) ◽  
Author(s):  
Ugur Gunduz
Keyword(s):  
Social Media ◽  
Sentiment Analysis ◽  
Disaster Management ◽  
Semantic Analysis ◽  
Global Epidemic ◽  
Social Media Platforms ◽  
The Difference ◽  
Textual Content ◽  
The Impact ◽  
Media Data

With developing technology today, social media has entered every area of our lives. Many people come together and share in social media platforms without time and space restrictions. Social media has been in our lives so much lately. It is an undeniable fact that global outbreaks, which constitute an important part of our lives, are also affected by these networks and that they exist in these networks and share the users. The purpose of making this hashtag analysis is to reveal the difference in discourse and language while analyzing twitter data, while doing this, to evaluate the effects of a global epidemic crisis on language, message and crisis management with social media data. Sentiment analysis of tweets, on the other hand, objectives to take a look at the contents of these messages, to degree the feelings and feelings conveyed. This form of analysis is typically completed through amassing textual content data, then investigating the “sentiment” conveyed. Within the scope of our study, one hundred thousand twitter messages posted with the #stayhome hashtag between 23 May 2020 and 29 May 2020 were examined. The impact and reliability of social media in disaster management could be questioned by carrying out a content analysis based totally on the semantic analysis of the messages given on the Twitter posts with the phrases and frequencies used. Social media and Twitter content are increasingly more identified as treasured resources of public health signals concerning use in ailment surveillance and health disaster management.

Social Media-Based Data Collection and Analysis in Educational Research

2020 ◽  
pp. 54-77
Author(s):  
Liuli Huang
Keyword(s):  
Social Media ◽  
Data Collection ◽  
Educational Research ◽  
Media In Education ◽  
Social Media Data ◽  
Educational Processes ◽  
Data Collection And Analysis ◽  
Media Data ◽  
Social Media In Education

The past decades have brought many changes to education, including the role of social media in education. Social media data offer educational researchers first-hand insights into educational processes. This is different from most traditional and often obtrusive data collection methods (e.g., interviews and surveys). Many researchers have explored the role of social media in education, such as the value of social media in the classroom, the relationship between academic achievement and social media. However, the role of social media in educational research, including data collection and analysis from social media, has been examined to a far lesser degree. This study seeks to discuss the potential of social media for educational research. The purpose of this chapter is to illustrate the process of collecting and analyzing social media data through a pilot study of current math educational conditions.

Social Media to Social Media Analytics

2019 ◽  
Vol 10 (2) ◽  
pp. 57-70 ◽  
Author(s):  
Vikas Kumar ◽  
Pooja Nanda
Keyword(s):  
Social Media ◽  
Social Media Analytics ◽  
Social Media Data ◽  
Ethical Concerns ◽  
Ethical Implications ◽  
The Social ◽  
Social Media Platforms ◽  
The Individual ◽  
The Impact ◽  
Media Data

With the amplification of social media platforms, the importance of social media analytics has exponentially increased for many brands and organizations across the world. Tracking and analyzing the social media data has been contributing as a success parameter for such organizations, however, the data is being poorly harnessed. Therefore, the ethical implications of social media analytics need to be identified and explored for both the organizations and targeted users of social media data. The present work is an exploratory study to identify the various techno-ethical concerns of social media engagement, as well as social media analytics. The impact of these concerns on the individuals, organizations, and society as a whole are discussed. Ethical engagement for the most common social media platforms has been outlined with a number of specific examples to understand the prominent techno-ethical concerns. Both the individual and organizational perspectives have been taken into account to identify the implications of social media analytics.

The impact of social media on human interaction in an organisation based on real-time social media data

2019 ◽  
Vol 4 (3) ◽  
pp. 260
Author(s):  
Sharifah Sakinah Syed Ahmad ◽  
Anis Naseerah Binti Shaik Osman ◽  
Halizah Basiron
Keyword(s):  
Social Media ◽  
Real Time ◽  
Human Interaction ◽  
Social Media Data ◽  
The Impact ◽  
Media Data

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.

Information Visualizations as a Tool to Study Users’ Social Media Privacy Concerns

2018 ◽  
Author(s):  
Anatoliy Gruzd ◽  
Jenna Jacobson ◽  
Elizabeth Dubois
Keyword(s):  
Social Media ◽  
Online Survey ◽  
Job Applicants ◽  
Social Media Data ◽  
Privacy Concerns ◽  
Comfort Levels ◽  
People’S Attitudes ◽  
Media Data ◽  
Information Visualizations

The amount and complexity of data that can be accessed from social media has been increasing exponentially. We examine the value of using information visualizations as a tool to study people’s attitudes and perceptions regarding their social media data being used by third parties. In the context of using social media to screen job applicants, we investigate the role of visualizations in studying users’ social media privacy concerns. Utilizing an online survey of 454 participants, we compare participants’ comfort levels in relation to different types of publicly accessible social media data. The results partially support the supposition that analytical information based on some form of data analysis will receive a stronger reaction when accompanied by representative visualizations.

Social Network Integration in Document Summarization

2014 ◽  
pp. 139-162 ◽  
Author(s):  
Atefeh Farzindar
Keyword(s):  
Social Media ◽  
Social Networking ◽  
Semantic Analysis ◽  
Dynamic Network ◽  
Large Data ◽  
Automatic Summarization ◽  
Opinion Summarization ◽  
Event Based ◽  
Media Data

In this chapter, the author presents the new role of summarization in the dynamic network of social media and its importance in semantic analysis of social media and large data. The author introduces how summarization tasks can improve social media retrieval and event detection. The author discusses the challenges in social media data versus traditional documents. The author presents the approaches to social media summarization and methods for update summarization, network activities summarization, event-based summarization, and opinion summarization. The author reviews the existing evaluation metrics for summarization and the efforts on evaluation shared tasks on social data related tracks by ACL, TREC, TAC, and SemEval. In conclusion, the author discusses the importance of this dynamic discipline and great potential of automatic summarization in the coming decade, in the context of changes in mobile technology, cloud computing, and social networking.

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.

Sign in / Sign up

Export Citation Format

Share Document