Dynamics of Punjab state's tourist image: a social media analytics perspective

2021 ◽  
Vol 14 (3) ◽  
pp. 408
Author(s):  
Viput Ongsakul ◽  
Tanveer Kajla ◽  
Uju Violet Alola ◽  
Sahil Raj ◽  
Tran Tien Khoa
Keyword(s):  
Social Media ◽  
Social Media Analytics

Social Media Analytics in Education: What Is It, How Is It Useful, and What Does It Tell Us About How Schools Are Discussed in Social Media?

2014 ◽  
Vol 35 (1) ◽  
pp. 7-43 ◽  
Author(s):  
Dick M. Carpenter ◽  
Jenifer Walsh Robertson ◽  
Michele E. Johnson ◽  
Scott Blum
Keyword(s):  
Social Media ◽  
Social Media Analytics

How Social Media Analytics Can Save Businesses

2020 ◽  
Author(s):  
Jay Palmer ◽  
Kyle Revis ◽  
Yves Romain
Keyword(s):  
Social Media ◽  
Social Media Analytics

scholarly journals Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem

2021 ◽  
pp. 089443932110122
Author(s):  
Dennis Assenmacher ◽  
Derek Weber ◽  
Mike Preuss ◽  
André Calero Valdez ◽  
Alison Bradshaw ◽  
...  
Keyword(s):  
Social Media ◽  
Data Sharing ◽  
Algorithm Design ◽  
Computational Social Science ◽  
Evaluation Framework ◽  
Social Media Analytics ◽  
Data Sets ◽  
The Public ◽  
Research Areas ◽  
Media Data

Computational social science uses computational and statistical methods in order to evaluate social interaction. The public availability of data sets is thus a necessary precondition for reliable and replicable research. These data allow researchers to benchmark the computational methods they develop, test the generalizability of their findings, and build confidence in their results. When social media data are concerned, data sharing is often restricted for legal or privacy reasons, which makes the comparison of methods and the replicability of research results infeasible. Social media analytics research, consequently, faces an integrity crisis. How is it possible to create trust in computational or statistical analyses, when they cannot be validated by third parties? In this work, we explore this well-known, yet little discussed, problem for social media analytics. We investigate how this problem can be solved by looking at related computational research areas. Moreover, we propose and implement a prototype to address the problem in the form of a new evaluation framework that enables the comparison of algorithms without the need to exchange data directly, while maintaining flexibility for the algorithm design.

scholarly journals Social Media Analytics: A Case Study of Singapore General Election 2020

2020 ◽  
Author(s):  
Sebastian Zhi Tao Khoo ◽  
Leong Hock Ho ◽  
Ee Hong Lee ◽  
Danston Kheng Boon Goh ◽  
Zehao Zhang ◽  
...  
Keyword(s):  
Social Media ◽  
General Election ◽  
Social Media Analytics

scholarly journals Trends in Patient, Physician, and Public Perception of Ulnar Collateral Ligament Reconstruction Using Social Media Analytics

2021 ◽  
Vol 9 (3) ◽  
pp. 232596712199005
Author(s):  
Jonathan S. Yu ◽  
James B. Carr ◽  
Jacob Thomas ◽  
Julianna Kostas ◽  
Zhaorui Wang ◽  
...  
Keyword(s):  
Social Media ◽  
Public Perception ◽  
Ulnar Collateral Ligament ◽  
Return To Play ◽  
Social Media Analytics ◽  
Care Providers ◽  
Collateral Ligament ◽  
The Past ◽  
Positive Sentiment ◽  
Negative Sentiment

Background: Social media posts regarding ulnar collateral ligament (UCL) injuries and reconstruction surgeries have increased in recent years. Purpose: To analyze posts shared on Instagram and Twitter referencing UCL injuries and reconstruction surgeries to evaluate public perception and any trends in perception over the past 3 years. Study Design: Cross-sectional study. Methods: A search of a 3-year period (August 2016 and August 2019) of public Instagram and Twitter posts was performed. We searched for >22 hashtags and search terms, including #TommyJohn, #TommyJohnSurgery, and #tornUCL. A categorical classification system was used to assess the sentiment, media format, perspective, timing, accuracy, and general content of each post. Post popularity was measured by number of likes and comments. Results: A total of 3119 Instagram posts and 267 Twitter posts were included in the analysis. Of the 3119 Instagram posts analyzed, 34% were from patients, and 28% were from providers. Of the 267 Twitter posts analyzed, 42% were from patients, and 16% were from providers. Although the majority of social media posts were of a positive sentiment, over the past 3 years, there was a major surge in negative sentiment posts (97% increase) versus positive sentiment posts (9% increase). Patients were more likely to focus their posts on rehabilitation, return to play, and activities of daily living. Providers tended to focus their posts on education, rehabilitation, and injury prevention. Patient posts declined over the past 3 years (–28%), whereas provider posts increased substantially (110%). Of posts shared by health care providers, 4% of posts contained inaccurate or misleading information. Conclusion: The majority of patients who post about their UCL injury and reconstruction on social media have a positive sentiment when discussing their procedure. However, negative sentiment posts have increased significantly over the past 3 years. Patient content revolves around rehabilitation and return to play. Although patient posts have declined over the past 3 years, provider posts have increased substantially with an emphasis on education.

scholarly journals A Bilingual Comparison of Sentiment and Topics for a Product Event on Twitter

2021 ◽  
Author(s):  
Irina Wedel ◽  
Michael Palk ◽  
Stefan Voß
Keyword(s):  
Social Media ◽  
Language Processing ◽  
Topic Modeling ◽  
New Product ◽  
Business Value ◽  
Data Driven ◽  
New Product Introduction ◽  
Social Media Analytics ◽  
Product Introduction ◽  
Textual Data

AbstractSocial media enable companies to assess consumers’ opinions, complaints and needs. The systematic and data-driven analysis of social media to generate business value is summarized under the term Social Media Analytics which includes statistical, network-based and language-based approaches. We focus on textual data and investigate which conversation topics arise during the time of a new product introduction on Twitter and how the overall sentiment is during and after the event. The analysis via Natural Language Processing tools is conducted in two languages and four different countries, such that cultural differences in the tonality and customer needs can be identified for the product. Different methods of sentiment analysis and topic modeling are compared to identify the usability in social media and in the respective languages English and German. Furthermore, we illustrate the importance of preprocessing steps when applying these methods and identify relevant product insights.

Public relations in the age of data: corporate perspectives on social media analytics (SMA)

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kathy R. Fitzpatrick ◽  
Paula L. Weissman
Keyword(s):  
Social Media ◽  
Public Relations ◽  
Social Media Analytics ◽  
Content Type ◽  
The Public ◽  
Management Function ◽  
Use Of Social Media ◽  
The Impact ◽  
Corporate Brands ◽  
Depth Interviews

PurposeThe 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/approachThe research involved in-depth interviews with chief communication officers (CCOs) from leading multinational corporate brands.FindingsThe 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/valueThe study is among the first to provide empirical evidence of how companies are using social media analytics to enhance public relations efforts.

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