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Social and Behavioral Sciences Commons™
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Articles 1 - 9 of 9
Full-Text Articles in Social and Behavioral Sciences
Happy Toilet: A Social Analytics Approach To The Study Of Public Toilet Cleanliness, Eugene W. J. Choy, Winston M. K. Ho, Xiaohang Li, Ragini Verma, Li Jin Sim, Kyong Jin Shim
Happy Toilet: A Social Analytics Approach To The Study Of Public Toilet Cleanliness, Eugene W. J. Choy, Winston M. K. Ho, Xiaohang Li, Ragini Verma, Li Jin Sim, Kyong Jin Shim
Research Collection School Of Computing and Information Systems
This study presents a social analytics approach to the study of public toilet cleanliness in Singapore. From popular social media platforms, our system automatically gathers and analyzes relevant public posts that mention about toilet cleanliness in highly frequented locations across the Singapore island - from busy shopping malls to food 'hawker' centers.
Of Promoting Networking And Protecting Privacy: Effects Of Defaults And Regulatory Focus On Social Media Users’ Preference Settings, Hichang Cho, Sungjong Roh, Byungho Park
Of Promoting Networking And Protecting Privacy: Effects Of Defaults And Regulatory Focus On Social Media Users’ Preference Settings, Hichang Cho, Sungjong Roh, Byungho Park
Research Collection Lee Kong Chian School Of Business
Privacy research has debated whether privacy decision-making is determined by users' stable preferences (i.e., individual traits), privacy calculus (i.e., cost-benefit analysis), or “responses on the spot” that vary across contexts. This study focuses on two factors—default setting as a contextual factor and regulatory focus as an individual difference factor—and examines the degree to which these factors affect social media users' decision-making when using privacy preference settings in a fictitious social networking site. The results, based on two experimental studies (study 1, n = 414; study 2, n = 213), show that default settings significantly affect users' privacy preferences, such that …
Predicting Audience Engagement Across Social Media Platforms In The News Domain, Kholoud Khalil Aldous, Jisun An, Bernard J. Jansen
Predicting Audience Engagement Across Social Media Platforms In The News Domain, Kholoud Khalil Aldous, Jisun An, Bernard J. Jansen
Research Collection School Of Computing and Information Systems
We analyze cross-platform factors for posts on both single and multiple social media platforms for numerous news outlets to better predict audience engagement, precisely the number of likes and comments. We collect 676,779 social media posts from 53 news outlets during eight months on four social media platforms (Facebook, Instagram, Twitter, and YouTube), along with the associated comments (more than 31 million) and the number of likes (more than 840 million). We develop a framework for predicting the audience engagement based on both linguistic features of the post and social media platform factors. Among other findings, results show that content …
Do Firms Manage Their Csr Reputation? Evidence From Twitter, Richard M. Crowley, Wenli Huang, Hai Lu, Wei Luo
Do Firms Manage Their Csr Reputation? Evidence From Twitter, Richard M. Crowley, Wenli Huang, Hai Lu, Wei Luo
Research Collection School Of Accountancy
Using a machine learning approach to process 11 million tweets posted by S&P 1500 firms from 2011 through 2016, we find that poor CSR performance firms tweet more about CSR activities and use tweets that are shorter, and with more passive voice and extreme tone. Good CSR performance firms tweet less about CSR, yet gain twice more followers per CSR tweet than poor CSR performance firms. Good CSR performance firms also experience a greater decrease in institutional ownership along with higher increases in bid-ask spread and stock return volatility after joining Twitter than do poor CSR performance firms. Our findings …
Authentic Leadership In The Digital Age, Richard R. Smith
Authentic Leadership In The Digital Age, Richard R. Smith
Research Collection Lee Kong Chian School Of Business
Artificial intelligence algorithms are actively assessing our personality and behaviour based on our social media footprint with amazing accuracy – even after we have retired or died.
Evaluating Vulnerability To Fake News In Social Networks: A Community Health Assessment Model, Bhavtosh Rath, Wei Gao, Jaideep Srivastava
Evaluating Vulnerability To Fake News In Social Networks: A Community Health Assessment Model, Bhavtosh Rath, Wei Gao, Jaideep Srivastava
Research Collection School Of Computing and Information Systems
Understanding the spread of false information in social networks has gained a lot of recent attention. In this paper, we explore the role community structures play in determining how people get exposed to fake news. Inspired by approaches in epidemiology, we propose a novel Community Health Assessment model, whose goal is to understand the vulnerability of communities to fake news spread. We define the concepts of neighbor, boundary and core nodes of a community and propose appropriate metrics to quantify the vulnerability of nodes (individual-level) and communities (group-level) to spreading fake news. We evaluate our model on communities identified using …
Mocked And Shamed: Satirical News And Its Effects On Organizational Reputation, Lisbeth Lim, Juliana Chia, Augustine Pang
Mocked And Shamed: Satirical News And Its Effects On Organizational Reputation, Lisbeth Lim, Juliana Chia, Augustine Pang
Research Collection Lee Kong Chian School Of Business
With fake news the rage (Tavernise, 2016), this study examines one form of fake news, satire news (Reilly, 2010). This study examines factors that lead satire news to be created, how they are used to criticize organizations and the impact on reputations. News on five satire news sites – The Onion (US), New Nation (Singapore), The Shovel (Australia), NewsThump (UK), and Der Postillon (Germany) – were analyzed using social media monitoring tools. Findings suggested that crises or paracrises (Coombs & Holladay, 2012) were likely to be exacerbated. While its effects are not immediate, satire news may have impact on organizations’ …
View, Like, Comment, Post: Analyzing User Engagement By Topic At 4 Levels Across 5 Social Media Platforms For 53 News Organizations, Kholoud K. Aldous, Jisun An, Bernard J. Jansen
View, Like, Comment, Post: Analyzing User Engagement By Topic At 4 Levels Across 5 Social Media Platforms For 53 News Organizations, Kholoud K. Aldous, Jisun An, Bernard J. Jansen
Research Collection School Of Computing and Information Systems
We evaluate the effects of the topics of social media posts on audiences across five social media platforms (i.e., Facebook, Instagram, Twitter, YouTube, and Reddit) at four levels of user engagement. We collected 3,163,373 social posts from 53 news organizations across five platforms during an 8month period. We analyzed the differences in news organization platform strategies by focusing on topic variations by organization and the corresponding effect on user engagement at four levels. Findings show that topic distribution varies by platform, although there are some topics that are popular across most platforms. User engagement levels vary both by topics and …
Evolution Of Corporate Reputation During An Evolving Controversy, Siyoung Chung, Mark Chong, Jie Sheng Chua, Ji Cheon Na
Evolution Of Corporate Reputation During An Evolving Controversy, Siyoung Chung, Mark Chong, Jie Sheng Chua, Ji Cheon Na
Research Collection Lee Kong Chian School Of Business
Purpose: The purpose of this paper is to investigate the evolution of online sentiments toward a company (i.e. Chipotle) during a crisis, and the effects of corporate apology on those sentiments. Design/methodology/approach: Using a very large data set of tweets (i.e. over 2.6m) about Company A’s food poisoning case (2015–2016). This case was selected because it is widely known, drew attention from various stakeholders and had many dynamics (e.g. multiple outbreaks, and across different locations). This study employed a supervised machine learning approach. Its sentiment polarity classification and relevance classification consisted of five steps: sampling, labeling, tokenization, augmentation of semantic …