Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Social media (4)
- Analytics (2)
- Social Media (2)
- #MeToo (1)
- Alternative Media (1)
-
- Asia Pacific (1)
- Consumer Pressure (1)
- Customer Service (1)
- Disasters (1)
- Facebook (1)
- Fact checking (1)
- Fake news (1)
- Mainstream Media (1)
- Neural attention (1)
- Neural networks (1)
- Online discussion (1)
- Peer Influence (1)
- Propagation tree (1)
- Public Figures (1)
- Recursive neural networks (1)
- Reddit (1)
- Rumor detection and classification (1)
- Rumors (1)
- Semi-supervised Learning (1)
- Sentiment analysis (1)
- Sexual harassment (1)
- Singapore (1)
- Singapore general election (1)
- Social listening (1)
- Social network analysis (1)
Articles 1 - 11 of 11
Full-Text Articles in Physical Sciences and Mathematics
Digital Social Listening On Conversations About Sexual Harassment, Xuesi Sim, Ern Rae Chang, Yu Xiang Ong, Jie Ying Yeo, Christine Bai Shuang Yan, Eugene Wen Jia Choy, Kyong Jin Shim
Digital Social Listening On Conversations About Sexual Harassment, Xuesi Sim, Ern Rae Chang, Yu Xiang Ong, Jie Ying Yeo, Christine Bai Shuang Yan, Eugene Wen Jia Choy, Kyong Jin Shim
Research Collection School Of Computing and Information Systems
In light of the #MeToo movement and publicized sexual harassment incidents in Singapore in recent years, we built an analytics pipeline for performing digital social listening on conversations about sexual harassment for AWARE (Association of Women for Action and Research). Our social network analysis results identified key influencers that AWARE can engage for sexual harassment awareness campaigns. Further, our analysis results suggest new hashtags that AWARE can use to run social media campaigns and achieve greater reach.
Identifying And Characterizing Alternative News Media On Facebook, Samuel S. Guimaraes, Julia C. S. Reis, Lucas Lima, Filipe N. Ribeiro, Marisa Vasconcelos, Jisun An, Haewoon Kwak, Fabricio Benevenuto
Identifying And Characterizing Alternative News Media On Facebook, Samuel S. Guimaraes, Julia C. S. Reis, Lucas Lima, Filipe N. Ribeiro, Marisa Vasconcelos, Jisun An, Haewoon Kwak, Fabricio Benevenuto
Research Collection School Of Computing and Information Systems
As Internet users increasingly rely on social media sites to receive news, they are faced with a bewildering number of news media choices. For example, thousands of Facebook pages today are registered and categorized as some form of news media outlets. This situation boosted the so-called independent journalism, also known as alternative news media. Identifying and characterizing all the news pages that play an important role in news dissemination is key for understanding the news ecosystems of a country. In this work, we propose a graph-based semi-supervised method to measure the political bias of pages on most countries and show …
Business Practice Of Social Media - Platform And Customer Service Adoption, Shujing Sun, Yang Gao, Huaxia Rui
Business Practice Of Social Media - Platform And Customer Service Adoption, Shujing Sun, Yang Gao, Huaxia Rui
Research Collection School Of Computing and Information Systems
This paper examines the key drivers in business adoptions of the platform and customer service within the context of social media. We carry out the empirical analyses using the decision trajectories of the international airline industry on Twitter. We find that a firm's decision-making is subject to both peer influence and consumer pressure. Regarding peer influence, we find that the odds of both adoptions increase when the extent of peers' adoption increases. We also identify the distinctive role of consumers. Specifically, before the platform adoption, firms learn about potential consequences from consumer reactions to peers' adoptions. Upon the platform adoption, …
Social Media Analytics: A Case Study Of Singapore General Election 2020, Sebastian Zhi Tao Khoo, Leong Hock Ho, Ee Hong Lee, Danston Kheng Boon Goh, Zehao Zhang, Swee Hong Ng, Haodi Qi, Kyong Jin Shim
Social Media Analytics: A Case Study Of Singapore General Election 2020, Sebastian Zhi Tao Khoo, Leong Hock Ho, Ee Hong Lee, Danston Kheng Boon Goh, Zehao Zhang, Swee Hong Ng, Haodi Qi, Kyong Jin Shim
Research Collection School Of Computing and Information Systems
The 2020 Singaporean General Election (GE2020) was a general election held in Singapore on July 10, 2020. In this study, we present an analysis on social conversations about GE2020 during the election period. We analyzed social conversations from popular platforms such as Twitter, HardwareZone, and TR Emeritus.
Adelaidecyc At Semeval-2020 Task 12: Ensemble Of Classifiers For Offensive Language Detection In Social Media, Mahen Herath, Thushari Atapattu, Hoang Anh Dung, Christoph Treude, Katrina Falkner
Adelaidecyc At Semeval-2020 Task 12: Ensemble Of Classifiers For Offensive Language Detection In Social Media, Mahen Herath, Thushari Atapattu, Hoang Anh Dung, Christoph Treude, Katrina Falkner
Research Collection School Of Computing and Information Systems
This paper describes the systems our team (AdelaideCyC) has developed for SemEval Task 12 (OffensEval 2020) to detect offensive language in social media. The challenge focuses on three subtasks – offensive language identification (subtask A), offense type identification (subtask B), and offense target identification (subtask C). Our team has participated in all the three subtasks. We have developed machine learning and deep learning-based ensembles of models. We have achieved F1-scores of 0.906, 0.552, and 0.623 in subtask A, B, and C respectively. While our performance scores are promising for subtask A, the results demonstrate that subtask B and C still …
A Tripartite Model Of Trust In Facebook: Acceptance Of Information Personalization, Privacy Concern, And Privacy Literacy, Sonny Rosenthal, Ole-Christian Wasenden, Gorm-Andreas Gronnevet, Rich Ling
A Tripartite Model Of Trust In Facebook: Acceptance Of Information Personalization, Privacy Concern, And Privacy Literacy, Sonny Rosenthal, Ole-Christian Wasenden, Gorm-Andreas Gronnevet, Rich Ling
Research Collection College of Integrative Studies
This study draws on the mental accounting perspective and a tripartite model of trust to explain why users trust Facebook. We argue that trust in Facebook is related to (1) trust in companies that collect personal data, (2) acceptance of information personalization, (3) low privacy concern, and (4) low privacy literacy. Further, we argue that privacy literacy amplifies the relationship between privacy concern and the other factors. This is because, among individuals with high privacy literacy, privacy concern is especially diagnostic of the potential harms of a loss of privacy. These arguments align broadly with theorizations about factors influencing privacy-related …
Coupled Hierarchical Transformer For Stance-Aware Rumor Verification In Social Media Conversations, Jianfei Yu, Jing Jiang, Ling Min Serena Khoo, Hai Leong Chieu, Rui Xia
Coupled Hierarchical Transformer For Stance-Aware Rumor Verification In Social Media Conversations, Jianfei Yu, Jing Jiang, Ling Min Serena Khoo, Hai Leong Chieu, Rui Xia
Research Collection School Of Computing and Information Systems
The prevalent use of social media enables rapid spread of rumors on a massive scale, which leads to the emerging need of automatic rumor verification (RV). A number of previous studies focus on leveraging stance classification to enhance RV with multi-task learning (MTL) methods. However, most of these methods failed to employ pre-trained contextualized embeddings such as BERT, and did not exploit inter-task dependencies by using predicted stance labels to improve the RV task. Therefore, in this paper, to extend BERT to obtain thread representations, we first propose a Hierarchical Transformer1 , which divides each long thread into shorter subthreads, …
We Mind Your Well-Being: Preventing Depression In Uncertain Social Networks By Sequential Interventions, Aye Phye Phye Aung, Xinrun Wang, Bo An, Xiaoli Li
We Mind Your Well-Being: Preventing Depression In Uncertain Social Networks By Sequential Interventions, Aye Phye Phye Aung, Xinrun Wang, Bo An, Xiaoli Li
Research Collection School Of Computing and Information Systems
Mental health has become a major concern according to WHO who estimates that more than 350 million people worldwide are affected by depression. Studies have shown that interventions and social support can reduce stress and depression. However, counselling centers do not have enough resources to provide counselling and social support to all the participants in their interest. This paper helps social support organizations (e.g., university counselling centers) sequentially select the participants for interventions. Unfortunately, previous works do not consider emotion propagation from other neighbours of the influencees and initial uncertainties of mental states and influence. Moreover, they fail to scale …
An Attention-Based Rumor Detection Model With Tree-Structured Recursive Neural Networks, Jing Ma, Wei Gao, Shafiq Joty, Kam-Fai Wong
An Attention-Based Rumor Detection Model With Tree-Structured Recursive Neural Networks, Jing Ma, Wei Gao, Shafiq Joty, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Rumor spread in social media severely jeopardizes the credibility of online content. Thus, automatic debunking of rumors is of great importance to keep social media a healthy environment. While facing a dubious claim, people often dispute its truthfulness sporadically in their posts containing various cues, which can form useful evidence with long-distance dependencies. In this work, we propose to learn discriminative features from microblog posts by following their non-sequential propagation structure and generate more powerful representations for identifying rumors. For modeling non-sequential structure, we first represent the diffusion of microblog posts with propagation trees, which provide valuable clues on how …
Are These Comments Triggering? Predicting Triggers Of Toxicity In Online Discussions, Hind Almerekhi, Haewoon Kwak, Joni Salminen, Bernard J. Jansen
Are These Comments Triggering? Predicting Triggers Of Toxicity In Online Discussions, Hind Almerekhi, Haewoon Kwak, Joni Salminen, Bernard J. Jansen
Research Collection School Of Computing and Information Systems
Understanding the causes or triggers of toxicity adds a new dimension to the prevention of toxic behavior in online discussions. In this research, we define toxicity triggers in online discussions as a non-toxic comment that lead to toxic replies. Then, we build a neural network-based prediction model for toxicity trigger. The prediction model incorporates text-based features and derived features from previous studies that pertain to shifts in sentiment, topic flow, and discussion context. Our findings show that triggers of toxicity contain identifiable features and that incorporating shift features with the discussion context can be detected with a ROC-AUC score of …
Detecting Fake News In Social Media: An Asia-Pacific Perspective, Meeyoung Cha, Wei Gao, Cheng-Te Li
Detecting Fake News In Social Media: An Asia-Pacific Perspective, Meeyoung Cha, Wei Gao, Cheng-Te Li
Research Collection School Of Computing and Information Systems
In March 2011, the catastrophic accident known as "The Fukushima Daiichi nuclear disaster" took place, initiated by the Tohoku earthquake and tsunami in Japan. The only nuclear accident to receive a Level-7 classification on the International Nuclear Event Scale since the Chernobyl nuclear power plant disaster in 1986, the Fukushima event triggered global concerns and rumors regarding radiation leaks. Among the false rumors was an image, which had been described as a map of radioactive discharge emanating into the Pacific Ocean, as illustrated in the accompanying figure. In fact, this figure, depicting the wave height of the tsunami that followed, …