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Social and Behavioral Sciences Commons™
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- Keyword
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- Social media (6)
- Twitter (6)
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- Social Network Analysis (2)
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- Social networks (2)
- Age Prediction (1)
- Age topic model (1)
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- Audience segmentation (1)
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- Research Collection School Of Computing and Information Systems (23)
- Research Collection Office of Corporate Communications and Marketing (9)
- Dissertations and Theses Collection (Open Access) (4)
- Research Collection Lee Kong Chian School Of Business (3)
- Research Collection School of Social Sciences (2)
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Articles 1 - 30 of 43
Full-Text Articles in Social and Behavioral Sciences
Data Preparation For Social Network Mining And Analysis, Yazhe Wang
Data Preparation For Social Network Mining And Analysis, Yazhe Wang
Dissertations and Theses Collection (Open Access)
This dissertation studies the problem of preparing good-quality social network data for data analysis and mining. Modern online social networks such as Twitter, Facebook, and LinkedIn have rapidly grown in popularity. The consequent availability of a wealth of social network data provides an unprecedented opportunity for data analysis and mining researchers to determine useful and actionable information in a wide variety of fields such as social sciences, marketing, management, and security. However, raw social network data are vast, noisy, distributed, and sensitive in nature, which challenge data mining and analysis tasks in storage, efficiency, accuracy, etc. Many mining algorithms cannot …
Issues Of Social Data Analytics With A New Method For Sentiment Analysis Of Social Media Data, Zhaoxia Wang, Victor J. C. Tong, David Chan
Issues Of Social Data Analytics With A New Method For Sentiment Analysis Of Social Media Data, Zhaoxia Wang, Victor J. C. Tong, David Chan
Research Collection School of Social Sciences
Social media data consists of feedback, critiques and other comments that are posted online by internet users. Collectively, these comments may reflect sentiments that are sometimes not captured in traditional data collection methods such as administering a survey questionnaire. Thus, social media data offers a rich source of information, which can be adequately analyzed and understood. In this paper, we survey the extant research literature on sentiment analysis and discuss various limitations of the existing analytical methods. A major limitation in the large majority of existing research is the exclusive focus on social media data in the English language. There …
Extracting Interest Tags From Twitter User Biographies, Ying Ding, Jing Jiang
Extracting Interest Tags From Twitter User Biographies, Ying Ding, Jing Jiang
Research Collection School Of Computing and Information Systems
Twitter, one of the most popular social media platforms, has been studied from different angles. One of the important sources of information in Twitter is users’ biographies, which are short self-introductions written by users in free form. Biographies often describe users’ background and interests. However, to the best of our knowledge, there has not been much work trying to extract information from Twitter biographies. In this work, we study how to extract information revealing users’ personal interests from Twitter biographies. A sequential labeling model is trained with automatically constructed labeled data. The popular patterns expressing user interests are extracted and …
Anomaly Detection Through Enhanced Sentiment Analysis On Social Media Data, Zhaoxia Wang, Victor Joo, Chuan Tong, Xin Xin, Hoong Chor Chin
Anomaly Detection Through Enhanced Sentiment Analysis On Social Media Data, Zhaoxia Wang, Victor Joo, Chuan Tong, Xin Xin, Hoong Chor Chin
Research Collection School Of Computing and Information Systems
Anomaly detection in sentiment analysis refers to detecting abnormal opinions, sentiment patterns or special temporal aspects of such patterns in a collection of data. The anomalies detected may be due to sudden sentiment changes hidden in large amounts of text. If these anomalies are undetected or poorly managed, the consequences may be severe, e.g. A business whose customers reveal negative sentiments and will no longer support the establishment. Social media platforms, such as Twitter, provide a vast source of information, which includes user feedback, opinion and information on most issues. Many organizations also leverage social media platforms to publish information …
Emotional Disclosure On Social Networking Sites: The Role Of Network Structure And Psychological Needs, Han Lin, William Tov, Lin Qiu
Emotional Disclosure On Social Networking Sites: The Role Of Network Structure And Psychological Needs, Han Lin, William Tov, Lin Qiu
Research Collection School of Social Sciences
We conducted three studies to understand how online emotional disclosure is influenced by social network structure on Facebook. Results showed that emotional disclosure was associated with both the density and size of users’ personal networks. Facebook users with denser networks disclosed more positive and negative emotions, and the relation between network density and emotional disclosure was mediated by stronger need for emotional expression. Facebook users with larger networks on Facebook disclosed more positive emotions, and the relation between network size and emotional disclosure was mediated by a stronger need for impression management. Our study extends past research by revealing the …
Goenawan Mohamad [Indonesia, Editor Of Tempo], Goenawan Mohamad
Goenawan Mohamad [Indonesia, Editor Of Tempo], Goenawan Mohamad
Digital Narratives of Asia
Goenawan Mohamad is the founder of Indonesia's Tempo magazine and a leading voice of democracy in the country. As founding editor, Mr Goenawan had to make the tough call of whether to continue Tempo's critical reporting of the government and face a ban, or toe the line to ensure survival. DNA talks to him about how he came to his decision and stuck to his principles, as well as his take on the many Indonesian leaders he has observed.
Identifying The High-Value Social Audience From Twitter Through Text-Mining Methods, Siaw Ling Lo, David Cornforth, Raymond Chiong
Identifying The High-Value Social Audience From Twitter Through Text-Mining Methods, Siaw Ling Lo, David Cornforth, Raymond Chiong
Research Collection School Of Computing and Information Systems
Doing business on social media has become a common practice for many companies these days. While the contents shared on Twitter and Facebook offer plenty of opportunities to uncover business insights, it remains a challenge to sift through the huge amount of social media data and identify the potential social audience who is highly likely to be interested in a particular company. In this paper, we analyze the Twitter content of an account owner and its list of followers through various text mining methods, which include fuzzy keyword matching, statistical topic modeling and machine learning approaches. We use tweets of …
On Joint Modeling Of Topical Communities And Personal Interest In Microblogs, Tuan-Anh Hoang, Ee Peng Lim
On Joint Modeling Of Topical Communities And Personal Interest In Microblogs, Tuan-Anh Hoang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
In this paper, we propose the Topical Communities and Personal Interest (TCPI) model for simultaneously modeling topics, topical communities, and users’ topical interests in microblogging data. TCPI considers different topical communities while differentiating users’ personal topical interests from those of topical communities, and learning the dependence of each user on the affiliated communities to generate content. This makes TCPI different from existing models that either do not consider the existence of multiple topical communities, or do not differentiate between personal and community’s topical interests. Our experiments on two Twitter datasets show that TCPI can effectively mine the representative topics for …
Entity Linking On Microblogs With Spatial And Temporal Signals, Yuan Fang, Ming-Wei Chang
Entity Linking On Microblogs With Spatial And Temporal Signals, Yuan Fang, Ming-Wei Chang
Research Collection School Of Computing and Information Systems
Microblogs present an excellent opportunity for monitoring and analyzing world happenings. Given that words are often ambiguous, entity linking becomes a crucial step towards understanding microblogs. In this paper, we re-examine the problem of entity linking on microblogs. We first observe that spatiotemporal (i.e., spatial and temporal) signals play a key role, but they are not utilized in existing approaches. Thus, we propose a novel entity linking framework that incorporates spatiotemporal signals through a weakly supervised process. Using entity annotations1 on real-world data, our experiments show that the spatiotemporal model improves F1 by more than 10 points over existing systems. …
Sharing Political News: The Balancing Act Of Intimacy And Socialization In Selective Exposure, Jisun An, Daniele Quercia, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft
Sharing Political News: The Balancing Act Of Intimacy And Socialization In Selective Exposure, Jisun An, Daniele Quercia, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft
Research Collection School Of Computing and Information Systems
One might think that, compared to traditional media, social media sites allow people to choose more freely what to read and what to share, especially for politically oriented news. However, reading and sharing habits originate from deeply ingrained behaviors that might be hard to change. To test the extent to which this is true, we propose a Political News Sharing (PoNS) model that holistically captures four key aspects of social psychology: gratification, selective exposure, socialization, and trust & intimacy. Using real instances of political news sharing in Twitter, we study the predictive power of these features. As one might expect, …
Clear: A Real-Time Online Observatory For Bursty And Viral Events, Runquan Xie, Feida Zhu, Hui Ma, Wei Xie, Chen Lin
Clear: A Real-Time Online Observatory For Bursty And Viral Events, Runquan Xie, Feida Zhu, Hui Ma, Wei Xie, Chen Lin
Research Collection School Of Computing and Information Systems
We describe our demonstration of CLEar (Clairaudient Ear), a real-time online platform for detecting, monitoring, summarizing, contextualizing and visualizing bursty and viral events, those triggering a sudden surge of public interest and going viral on micro-blogging platforms. This task is challenging for existing methods as they either use complicated topic models to analyze topics in a off-line manner or define temporal structure of fixed granularity on the data stream for online topic learning, leaving them hardly scalable for real-time stream like that of Twitter. In this demonstration of CLEar, we present a three-stage system: First, we show …
Interestingness-Driven Diffussion Process Summarization In Dynamic Networks, Qiang Qu, Siyuan Liu, Christian Jensen, Feida Zhu, Christos Faloutsos
Interestingness-Driven Diffussion Process Summarization In Dynamic Networks, Qiang Qu, Siyuan Liu, Christian Jensen, Feida Zhu, Christos Faloutsos
Research Collection School Of Computing and Information Systems
The widespread use of social networks enables the rapid diffusion of information, e.g., news, among users in very large communities. It is a substantial challenge to be able to observe and understand such diffusion processes, which may be modeled as networks that are both large and dynamic. A key tool in this regard is data summarization. However, few existing studies aim to summarize graphs/networks for dynamics. Dynamic networks raise new challenges not found in static settings, including time sensitivity and the needs for online interestingness evaluation and summary traceability, which render existing techniques inapplicable. We study the topic of dynamic …
An Exploratory Study On Software Microblogger Behaviors, Yuan Tian, David Lo
An Exploratory Study On Software Microblogger Behaviors, Yuan Tian, David Lo
Research Collection School Of Computing and Information Systems
Microblogging services are growing rapidly in the recent years. Twitter, one of the most popular microblogging sites, has gained more than 500 millions users. Thousands of developers are also using Twitter to communicate with one another and microblog about software-related topics such as programming languages, code libraries, etc. Understanding the behaviors of software microbloggers is one of the needed first steps toward building automated tools to encourage software microblogging activities and harness software microblogging to improve various software engineering activities. In this paper, we investigate the behaviors of software microbloggers in terms of their microblogging frequency, generated contents, and interactions …
A Study Of Age Gaps Between Online Friends, Lizi Liao, Jing Jiang, Ee Peng Lim, Heyan Huang
A Study Of Age Gaps Between Online Friends, Lizi Liao, Jing Jiang, Ee Peng Lim, Heyan Huang
Research Collection School Of Computing and Information Systems
User attribute extraction on social media has gain considerable attention, while existing methods are mostly supervised which suffer great diffi- culty in insufficient gold standard data. In this paper, we validate a strong hypothesis based on homophily and adapt it to ensure the certainty of user attribute we extracted via weakly supervised propagation. Homophily, the theory which states that people who are similar tend to become friends, has been well studied in the setting of online social networks. When we focus on age attribute, based on this theory, online friends tend to have similar age. In this work, we take …
Opinion Mining Of Sociopolitical Comments From Social Media, Swapna Gottipati
Opinion Mining Of Sociopolitical Comments From Social Media, Swapna Gottipati
Dissertations and Theses Collection (Open Access)
Opinions are central to almost all human activities by influencing greatly the decision making process. In this thesis, we present the problems of mining issues, extracting entities and suggestive opinions towards the entities, detecting thoughtful comments, and extracting stances and ideological expressions from online comments in the sociopolitical domain. This study is essential for opinion mining applications that are beneficial for policy makers, government sectors and social organizations. Much work has been done to try to uncover consumer sentiments from online comments to help businesses improve their products and services. However, sociopolitical opinion mining poses new challenges due to complex …
Diversified Social Influence Maximization, Fangshuang Tang, Qi Liu, Hengshu Zhu, Enhong Chen, Feida Zhu
Diversified Social Influence Maximization, Fangshuang Tang, Qi Liu, Hengshu Zhu, Enhong Chen, Feida Zhu
Research Collection School Of Computing and Information Systems
For better viral marketing, there has been a lot of research on social influence maximization. However, the problem that who is influenced and how diverse the influenced population is, which is important in real-world marketing, has largely been neglected. To that end, in this paper, we propose to consider the magnitude of influence and the diversity of the influenced crowd simultaneously. Specifically, we formulate it as an optimization problem, i.e., diversified social influence maximization. First, we present a general framework for this problem, under which we construct a class of diversity measures to quantify the diversity of the influenced crowd. …
On Macro And Micro Exploration Of Hashtag Diffusion In Twitter, Yazhe Wang, Baihua Zheng
On Macro And Micro Exploration Of Hashtag Diffusion In Twitter, Yazhe Wang, Baihua Zheng
Research Collection School Of Computing and Information Systems
This exploratory work studies hashtag diffusion in Twitter. The analysis is conducted from two aspects. From the macro perspective, we study general properties of hashtag diffusion, and classify hashtags into three main classes based on their temporal dynamics referred as 'single spike', 'multi-spikes', and 'fluctuation', and find that each of these classes has some unique characteristics. From the micro perspective, we investigate individual diffusion.We adopt Edelman's 'topology of influence' theory to identify four type of users with different influence levels in diffusion based on their dynamic retweet behaviors. The results of our study are useful for gaining more insights of …
Generating Supplementary Travel Guides From Social Media, Liu Yang, Jing Jiang, Lifu Huang, Minghui Qiu, Lizi Liao
Generating Supplementary Travel Guides From Social Media, Liu Yang, Jing Jiang, Lifu Huang, Minghui Qiu, Lizi Liao
Research Collection School Of Computing and Information Systems
In this paper we study how to summarize travel-related information in forum threads to generate supplementary travel guides. Such summaries presumably can provide additional and more up-to-date information to tourists. Existing multi-document summarization methods have limitations for this task because (1) they do not generate structured summaries but travel guides usually follow a certain template, and (2) they do not put emphasis on named entities but travel guides often recommend points of interest to travelers. To overcome these limitations, we propose to use a latent variable model to align forum threads with the section structure of well-written travel guides. The …
On Predicting Religion Labels In Microblogging Networks, Minh Thap Nguyen, Ee Peng Lim
On Predicting Religion Labels In Microblogging Networks, Minh Thap Nguyen, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Religious belief plays an important role in how people behave, influencing how they form preferences, interpret events around them, and develop relationships with others. Traditionally, the religion labels of user population are obtained by conducting a large scale census study. Such an approach is both high cost and time consuming. In this paper, we study the problem of predicting users' religion labels using their microblogging data. We formulate religion label prediction as a classification task, and identify content, structure and aggregate features considering their self and social variants for representing a user. We introduce the notion of representative user to …
Influences Of Influential Users: An Empirical Study Of Music Social Network, Jing Ren, Zhiyong Cheng, Jialie Shen, Feida Zhu
Influences Of Influential Users: An Empirical Study Of Music Social Network, Jing Ren, Zhiyong Cheng, Jialie Shen, Feida Zhu
Research Collection School Of Computing and Information Systems
Influential user can play a crucial role in online social networks. This paper documents an empirical study aiming at exploring the effects of influential users in the context of music social network. To achieve this goal, music diffusion graph is developed to model how information propagates over network. We also propose a heuristic method to measure users' influences. Using the real data from Last. fm, our empirical test demonstrates key effects of influential users and reveals limitations of existing influence identification/characterization schemes.
Lifetime Lexical Variation In Social Media, Lizi Liao, Jing Jiang, Ying Ding, Heyan Huang, Ee Peng Lim
Lifetime Lexical Variation In Social Media, Lizi Liao, Jing Jiang, Ying Ding, Heyan Huang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
As the rapid growth of online social media attracts a large number of Internet users, the large volume of content generated by these users also provides us with an opportunity to study the lexical variation of people of different ages. In this paper, we present a latent variable model that jointly models the lexical content of tweets and Twitter users’ ages. Our model inherently assumes that a topic has not only a word distribution but also an age distribution. We propose a Gibbs-EM algorithm to perform inference on our model. Empirical evaluation shows that our model can learn meaningful age-specific …
Impact Of Social Media On Power Relations Of Korean Health Activism, Kyu Jin Shim
Impact Of Social Media On Power Relations Of Korean Health Activism, Kyu Jin Shim
Research Collection Lee Kong Chian School Of Business
This case study explores how the Korea Leukemia Patient Group (KLPG) uses social media in its internal communication strategy and how that empowers its relationship with external counterparts. The findings of this study indicate that the local health NGO’s communication strategy is changing in response to the increased effectiveness and impact of social media. With the use of social media like Twitter, the KLPG can construct an issue-based advocacy group quickly and effectively. Consequently, more legitimacy and representativeness through collected support from general publics has further empowered the KLPG. Yet, the sustainability component in the relationships built through social media …
Predicting The Popularity Of Web 2.0 Items Based On User Comments, Xiangnan He, Ming Gao, Min-Yen Kan, Yiqun Liu, Kazunari Sugiyama
Predicting The Popularity Of Web 2.0 Items Based On User Comments, Xiangnan He, Ming Gao, Min-Yen Kan, Yiqun Liu, Kazunari Sugiyama
Research Collection School Of Computing and Information Systems
In the current Web 2.0 era, the popularity of Web resources fluctuates ephemerally, based on trends and social interest. As a result, content-based relevance signals are insufficient to meet users' constantly evolving information needs in searching for Web 2.0 items. Incorporating future popularity into ranking is one way to counter this. However, predicting popularity as a third party (as in the case of general search engines) is difficult in practice, due to their limited access to item view histories. To enable popularity prediction externally without excessive crawling, we propose an alternative solution by leveraging user comments, which are more accessible …
Women (And Men) Can Have It All, Singapore Management University
Women (And Men) Can Have It All, Singapore Management University
Perspectives@SMU
Value of caregiving must be recognised for men and women to be truly equal
Parasocial Relationship Via Reality Tv And Social Media: Its Implications For Celebrity Endorsement, Siyoung Chung, Hichang Cho
Parasocial Relationship Via Reality Tv And Social Media: Its Implications For Celebrity Endorsement, Siyoung Chung, Hichang Cho
Research Collection Lee Kong Chian School Of Business
The purpose of this study was to explore the ways in which audiences build parasocial relationships with media characters via reality TV and social media, and its implications for celebrity endorsement and purchase intentions. Using an online survey, this study collected 401 responses from the Korean Wave fans in Singapore. The results showed that reality TV viewing and SNS use to interact with media characters were positively associated with parasocial relationships between media characters and viewers. Parasocial relationships, in turn, were positively associated with the viewers’ perception of endorser and brand credibility, and purchase intention of the brand endorsed by …
Does Latitude Hurt While Longitude Kills? Geographical And Temporal Separation In A Large Scale Software Development Project, Patrick Wagstrom, Subhajit Datta
Does Latitude Hurt While Longitude Kills? Geographical And Temporal Separation In A Large Scale Software Development Project, Patrick Wagstrom, Subhajit Datta
Research Collection School Of Computing and Information Systems
Distributed software development allows firms to leverage cost advantages and place work near centers of competency. This distribution comes at a cost -- distributed teams face challenges from differing cultures, skill levels, and a lack of shared working hours. In this paper we examine whether and how geographic and temporal separation in a large scale distributed software development influences developer interactions. We mine the work item trackers for a large commercial software project with a globally distributed development team. We examine both the time to respond and the propensity of individuals to respond and find that when taken together, geographic …
Online Community Transition Detection, Biying Tan, Feida Zhu, Qiang Qu, Siyuan Liu
Online Community Transition Detection, Biying Tan, Feida Zhu, Qiang Qu, Siyuan Liu
Research Collection School Of Computing and Information Systems
Mining user behavior patterns in social networks is of great importance in user behavior analysis, targeted marketing, churn prediction and other applications. However, less effort has been made to study the evolution of user behavior in social communities. In particular, users join and leave communities over time. How to automatically detect the online community transitions of individual users is a research problem of immense practical value yet with great technical challenges. In this paper, we propose an algorithm based on the Minimum Description Length (MDL) principle to trace the evolution of community transition of individual users, adaptive to the noisy …
Socio-Physical Analytics: Challenges & Opportunities, Archan Misra, Kasthuri Jayarajah, Shriguru Nayak, Philips Kokoh Prasetyo, Ee-Peng Lim
Socio-Physical Analytics: Challenges & Opportunities, Archan Misra, Kasthuri Jayarajah, Shriguru Nayak, Philips Kokoh Prasetyo, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
In this paper, we argue for expanded research into an area called Socio-Physical Analytics, that focuses on combining the behavioral insight gained from mobile-sensing based monitoring of physical behavior with the inter-personal relationships and preferences deduced from online social networks. We highlight some of the research challenges in combining these heterogeneous data sources and then describe some examples of our ongoing work (based on real-world data being collected at SMU) that illustrate two aspects of socio-physical analytics: (a) how additional demographic and online analytics based attributes can potentially provide better insights into the preferences and behaviors of individuals or groups …
Media Frames And Cognitive Accessibility: What Do "Global Warming" And "Climate Change" Evoke Partisan Minds?, Jonathon P. Schuldt, Sungjong Roh
Media Frames And Cognitive Accessibility: What Do "Global Warming" And "Climate Change" Evoke Partisan Minds?, Jonathon P. Schuldt, Sungjong Roh
Research Collection Lee Kong Chian School Of Business
Decades of research demonstrate that how the public thinks about a given issue is affected by how it is framed by the media. Typically, studies of framing vary how an issue is portrayed (often, by altering the text of written communication) and compare subsequent beliefs, attitudes, or preferences—taking a framing effect as evidence that a media frame (or frame in communication) instantiated a particular audience frame (or frame in thought). Less work, however, has attempted to measure frames in thought directly, which may illuminate cognitive mechanisms that underlie framing effects. In this vein, we describe a Web experiment (n = …
On Modeling Community Behaviors And Sentiments In Microblogging, Tuan Anh Hoang, William Cohen, Ee Peng Lim
On Modeling Community Behaviors And Sentiments In Microblogging, Tuan Anh Hoang, William Cohen, Ee Peng Lim
Research Collection School Of Computing and Information Systems
In this paper, we propose the CBS topic model, a probabilistic graphical model, to derive the user communities in microblogging networks based on the sentiments they express on their generated content and behaviors they adopt. As a topic model, CBS can uncover hidden topics and derive user topic distribution. In addition, our model associates topic-specific sentiments and behaviors with each user community. Notably, CBS has a general framework that accommodates multiple types of behaviors simultaneously. Our experiments on two Twitter datasets show that the CBS model can effectively mine the representative behaviors and emotional topics for each community. We also …