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Articles 31 - 60 of 61
Full-Text Articles in Physical Sciences and Mathematics
Modeling Topics And Behavior Of Microbloggers: An Integrated Approach, Tuan Anh Hoang, Ee-Peng Lim
Modeling Topics And Behavior Of Microbloggers: An Integrated Approach, Tuan Anh Hoang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Microblogging encompasses both user-generated content and behavior. When modeling microblogging data, one has to consider personal and background topics, as well as how these topics generate the observed content and behavior. In this article, we propose the Generalized Behavior-Topic (GBT) model for simultaneously modeling background topics and users' topical interest in microblogging data. GBT considers multiple topical communities (or realms) with different background topical interests while learning the personal topics of each user and the user's dependence on realms to generate both content and behavior. This differentiates GBT from other previous works that consider either one realm only or content …
Inferring User Consumption Preferences From Social Media, Yang Li, Jing Jiang, Ting Liu
Inferring User Consumption Preferences From Social Media, Yang Li, Jing Jiang, Ting Liu
Research Collection School Of Computing and Information Systems
Social Media has already become a new arena of our lives and involved different aspects of our social presence. Users' personal information and activities on social media presumably reveal their personal interests, which offer great opportunities for many e-commerce applications. In this paper, we propose a principled latent variable model to infer user consumption preferences at the category level (e.g. inferring what categories of products a user would like to buy). Our model naturally links users' published content and following relations on microblogs with their consumption behaviors on e-commerce websites. Experimental results show our model outperforms the state-of-the-art methods significantly …
Fine-Grained Sentiment Analysis Of Social Media With Emotion Sensing, Zhaoxia Wang, Chee Seng Chong, Landy Lan, Yinping Yang, Beng-Seng Ho, Joo Chuan Tong
Fine-Grained Sentiment Analysis Of Social Media With Emotion Sensing, Zhaoxia Wang, Chee Seng Chong, Landy Lan, Yinping Yang, Beng-Seng Ho, Joo Chuan Tong
Research Collection School Of Computing and Information Systems
Social media is arguably the richest source of human generated text input. Opinions, feedbacks and critiques provided by internet users reflect attitudes and sentiments towards certain topics, products, or services. The sheer volume of such information makes it effectively impossible for any group of persons to read through. Thus, social media sentiment analysis has become an important area of work to make sense of the social media talk. However, most existing sentiment analysis techniques focus only on the aggregate level, classifying sentiments broadly into positive, neutral or negative, and lack the capabilities to perform fine-grained sentiment analysis. This paper describes …
On Profiling Bots In Social Media, Richard J. Oentaryo, Arinto Murdopo, Philips K. Prasetyo, Ee Peng Lim
On Profiling Bots In Social Media, Richard J. Oentaryo, Arinto Murdopo, Philips K. Prasetyo, Ee Peng Lim
Research Collection School Of Computing and Information Systems
The popularity of social media platforms such as Twitter has led to the proliferation of automated bots, creating both opportunities and challenges in information dissemination, user engagements, and quality of services. Past works on profiling bots had been focused largely on malicious bots, with the assumption that these bots should be removed. In this work, however, we find many bots that are benign, and propose a new, broader categorization of bots based on their behaviors. This includes broadcast, consumption, and spam bots. To facilitate comprehensive analyses of bots and how they compare to human accounts, we develop a systematic profiling …
Spiteful, One-Off, And Kind: Predicting Customer Feedback Behavior On Twitter, Agus Sulistya, Abhishek Sharma, David Lo
Spiteful, One-Off, And Kind: Predicting Customer Feedback Behavior On Twitter, Agus Sulistya, Abhishek Sharma, David Lo
Research Collection School Of Computing and Information Systems
Social media provides a convenient way for customers to express their feedback to companies. Identifying different types of customers based on their feedback behavior can help companies to maintain their customers. In this paper, we use a machine learning approach to predict a customer’s feedback behavior based on her first feedback tweet. First, we identify a few categories of customers based on their feedback frequency and the sentiment of the feedback. We identify three main categories: spiteful, one-off, and kind. Next, we build a model to predict the category of a customer given her first feedback. We use profile and …
Behavior Analysis In Social Networks: Challenges, Technologies, And Trends, Meng Wang, Ee-Peng Lim, Lei Li, Mehmet Orgun
Behavior Analysis In Social Networks: Challenges, Technologies, And Trends, Meng Wang, Ee-Peng Lim, Lei Li, Mehmet Orgun
Research Collection School Of Computing and Information Systems
The research on social networks has advanced significantly, which can be attributed to the prevalence of the online social websites and instant messaging systems as well as the popularity of mobile apps that support easy access to online social networks. These social networks are usually characterized by the complex network structures and rich contextual information. They now become the key platforms for, among others, content dissemination, professional networking, recommendation, alerting, and political campaigns. As online social network users perform activities on the social networks, they leave data traces of human behavior which allow the latter to be studied at scale. …
#Greysanatomy Vs. #Yankees: Demographics And Hashtag Use On Twitter, Jisun An, Ingmar Weber
#Greysanatomy Vs. #Yankees: Demographics And Hashtag Use On Twitter, Jisun An, Ingmar Weber
Research Collection School Of Computing and Information Systems
Demographics, in particular, gender, age, and race, are a key predictor of human behavior. Despite the significant effect that demographics plays, most scientific studies using online social media do not consider this factor, mainly due to the lack of such information. In this work, we use state-of-the-art face analysis software to infer gender, age, and race from profile images of 350K Twitter users from New York. For the period from November 1, 2014 to October 31, 2015, we study which hashtags are used by different demographic groups. Though we find considerable overlap for the most popular hashtags, there are also …
A Business Zone Recommender System Based On Facebook And Urban Planning Data, Jovian Lin, Richard Jayadi Oentaryo, Ee Peng Lim, Casey Vu, Adrian Wei Liang Vu, Philips Kokoh And Prasetyo
A Business Zone Recommender System Based On Facebook And Urban Planning Data, Jovian Lin, Richard Jayadi Oentaryo, Ee Peng Lim, Casey Vu, Adrian Wei Liang Vu, Philips Kokoh And Prasetyo
Research Collection School Of Computing and Information Systems
We present ZoneRec—a zone recommendation system for physical businesses in an urban city,which uses both public business data from Facebook and urban planning data. The systemconsists of machine learning algorithms that take in a business’ metadata and outputs a list ofrecommended zones to establish the business in. We evaluate our system using data of foodbusinesses in Singapore and assess the contribution of different feature groups to therecommendation quality.
Whom Should We Sense In 'Social Sensing' - Analyzing Which Users Work Best For Social Media Now-Casting, Jisun An, Ingmar Weber
Whom Should We Sense In 'Social Sensing' - Analyzing Which Users Work Best For Social Media Now-Casting, Jisun An, Ingmar Weber
Research Collection School Of Computing and Information Systems
Given the ever increasing amount of publicly available social media data, there is growing interest in using online data to study and quantify phenomena in the offline 'real' world. As social media data can be obtained in near real-time and at low cost, it is often used for 'now-casting' indices such as levels of flu activity or unemployment. The term 'social sensing' is often used in this context to describe the idea that users act as 'sensors', publicly reporting their health status or job losses. Sensor activity during a time period is then typically aggregated in a 'one tweet, one …
Chalk And Cheese In Twitter: Discriminating Personal And Organization Accounts, Richard Jayadi Oentaryo, Jia-Wei Low, Ee Peng Lim
Chalk And Cheese In Twitter: Discriminating Personal And Organization Accounts, Richard Jayadi Oentaryo, Jia-Wei Low, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Social media have been popular not only for individuals to share contents, but also for organizations to engage users and spread information. Given the trait differences between personal and organization accounts, the ability to distinguish between the two account types is important for developing better search/recommendation engines, marketing strategies, and information dissemination platforms. However, such task is non-trivial and has not been well studied thus far. In this paper, we present a new generic framework for classifying personal and organization accounts, based upon which comprehensive and systematic investigation on a rich variety of content, social, and temporal features can be …
Review Selection Using Micro-Reviews, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas
Review Selection Using Micro-Reviews, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas
Research Collection School Of Computing and Information Systems
Given the proliferation of review content, and the fact that reviews are highly diverse and often unnecessarily verbose, users frequently face the problem of selecting the appropriate reviews to consume. Micro-reviews are emerging as a new type of online review content in the social media. Micro-reviews are posted by users of check-in services such as Foursquare. They are concise (up to 200 characters long) and highly focused, in contrast to the comprehensive and verbose reviews. In this paper, we propose a novel mining problem, which brings together these two disparate sources of review content. Specifically, we use coverage of micro-reviews …
Review Synthesis For Micro-Review Summarization, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas
Review Synthesis For Micro-Review Summarization, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas
Research Collection School Of Computing and Information Systems
Micro-reviews is a new type of user-generated content arising from the prevalence of mobile devices and social media in the past few years. Micro-reviews are bite-size reviews (usually under 200 characters), commonly posted on social media or check-in services, using a mobile device. They capture the immediate reaction of users, and they are rich in information, concise, and to the point. However, the abundance of micro-reviews, and their telegraphic nature make it increasingly difficult to go through them and extract the useful information, especially on a mobile device. In this paper, we address the problem of summarizing the micro-reviews of …
Community Discovery From Social Media By Low-Rank Matrix Recovery, Jinfeng Zhuang, Mei Tao, Steven C. H. Hoi, Xian-Sheng Hua, Yongdong Zhang
Community Discovery From Social Media By Low-Rank Matrix Recovery, Jinfeng Zhuang, Mei Tao, Steven C. H. Hoi, Xian-Sheng Hua, Yongdong Zhang
Research Collection School Of Computing and Information Systems
The pervasive usage and reach of social media have attracted a surge of attention in the multimedia research community. Community discovery from social media has therefore become an important yet challenging issue. However, due to the subjective generating process, the explicitly observed communities (e.g., group-user and user-user relationship) are often noisy and incomplete in nature. This paper presents a novel approach to discovering communities from social media, including the group membership and user friend structure, by exploring a low-rank matrix recovery technique. In particular, we take Flickr as one exemplary social media platform. We first model the observed indicator matrix …
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 …
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 …
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 …
Partisan Sharing: Facebook Evidence And Societal Consequences, Jisun An, Daniele Quercia, Jon Crowcroft
Partisan Sharing: Facebook Evidence And Societal Consequences, Jisun An, Daniele Quercia, Jon Crowcroft
Research Collection School Of Computing and Information Systems
The hypothesis of selective exposure assumes that people seek out information that supports their views and eschew information that conflicts with their beliefs, and that has negative consequences on our society. Few researchers have recently found counter evidence of selective exposure in social media: users are exposed to politically diverse articles. No work has looked at what happens after exposure, particularly how individuals react to such exposure, though. Users might well be exposed to diverse articles but share only the partisan ones. To test this, we study partisan sharing on Facebook: the tendency for users to predominantly share like-minded news …
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, …
A Unified Model For Topics, Events And Users On Twitter, Qiming Diao, Jing Jiang
A Unified Model For Topics, Events And Users On Twitter, Qiming Diao, Jing Jiang
Research Collection School Of Computing and Information Systems
With the rapid growth of social media, Twitter has become one of the most widely adopted platforms for people to post short and instant message. On the one hand, people tweets about their daily lives, and on the other hand, when major events happen, people also follow and tweet about them. Moreover, people’s posting behaviors on events are often closely tied to their personal interests. In this paper, we try to model topics, events and users on Twitter in a unified way. We propose a model which combines an LDA-like topic model and the Recurrent Chinese Restaurant Process to capture …
Modeling Interaction Features For Debate Side Clustering, Minghui Qiu, Liu Yang, Jing Jiang
Modeling Interaction Features For Debate Side Clustering, Minghui Qiu, Liu Yang, Jing Jiang
Research Collection School Of Computing and Information Systems
Online discussion forums are popular social media platforms for users to express their opinions and discuss controversial issues with each other. To automatically identify the sides/stances of posts or users from textual content in forums is an important task to help mine online opinions. To tackle the task, it is important to exploit user posts that implicitly contain support and dispute (interaction) information. The challenge we face is how to mine such interaction information from the content of posts and how to use them to help identify stances. This paper proposes a two-stage solution based on latent variable models: an …
Your Love Is Public Now: Questioning The Use Of Personal Information In Authentication, Payas Gupta, Swapna Gottipati, Jing Jiang, Debin Gao
Your Love Is Public Now: Questioning The Use Of Personal Information In Authentication, Payas Gupta, Swapna Gottipati, Jing Jiang, Debin Gao
Research Collection School Of Computing and Information Systems
Most social networking platforms protect user's private information by limiting access to it to a small group of members, typically friends of the user, while allowing (virtually) everyone's access to the user's public data. In this paper, we exploit public data available on Facebook to infer users' undisclosed interests on their profile pages. In particular, we infer their undisclosed interests from the public data fetched using Graph APIs provided by Facebook. We demonstrate that simply liking a Facebook page does not corroborate that the user is interested in the page. Instead, we perform sentiment-oriented mining on various attributes of a …
Traditional Media Seen From Social Media, Jisun An, Daniele Quercia, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft
Traditional Media Seen From Social Media, Jisun An, Daniele Quercia, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft
Research Collection School Of Computing and Information Systems
With the advent of social media services, media outlets have started reaching audiences on social-networking sites. On Twitter, users actively follow a wide set of media sources, form interpersonal networks, and propagate interesting stories to their peers. These media subscription and interaction patterns, which had previously been hidden behind media corporations' databases, offer new opportunities to understand media supply and demand on a large scale. Through a map that connects 77 media outlets based on Twitter subscription patterns, we are able to answer a variety of questions: to what extent New York Times and the Wall Street Journal readers overlap? …
Fragmented Social Media: A Look Into Selective Exposure To Political News, Jisun An, Daniele Quercia, Jon Crowcroft
Fragmented Social Media: A Look Into Selective Exposure To Political News, Jisun An, Daniele Quercia, Jon Crowcroft
Research Collection School Of Computing and Information Systems
The hypothesis of selective exposure assumes that people crave like-minded information and eschew information that conflicts with their beliefs, and that has negative consequences on political life. Yet, despite decades of research, this hypothesis remains theoretically promising but empirically difficult to test. We look into news articles shared on Facebook and examine whether selective exposure exists or not in social media. We find a concrete evidence for a tendency that users predominantly share like-minded news articles and avoid conflicting ones, and partisans are more likely to do that. Building tools to counter partisanship on social media would require the ability …
Community-Based Classification Of Noun Phrases In Twitter, Freddy Chong Tat Chua, William W. Cohen, Justin Betterridge, Ee-Peng Lim
Community-Based Classification Of Noun Phrases In Twitter, Freddy Chong Tat Chua, William W. Cohen, Justin Betterridge, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Many event monitoring systems rely on counting known keywords in streaming text data to detect sudden spikes in frequency. But the dynamic and conversational nature of Twitter makes it hard to select known keywords for monitoring. Here we consider a method of automatically finding noun phrases (NPs) as keywords for event monitoring in Twitter. Finding NPs has two aspects, identifying the boundaries for the subsequence of words which represent the NP, and classifying the NP to a specific broad category such as politics, sports, etc. To classify an NP, we define the feature vector for the NP using not just …
Content Contribution For Revenue Sharing And Reputation: A Dynamic Structural Model, Qian Tang, Bin Gu, Andrew B. Whinston
Content Contribution For Revenue Sharing And Reputation: A Dynamic Structural Model, Qian Tang, Bin Gu, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
This study examines the incentives for content contribution in social media. We propose that exposure and reputation are the major incentives for contributors. Besides, as more and more social media Web sites offer advertising-revenue sharing with some of their contributors, shared revenue provides an extra incentive for contributors who have joined revenue-sharing programs. We develop a dynamic structural model to identify a contributor's underlying utility function from observed contribution behavior. We recognize the dynamic nature of the content-contribution decision-that contributors are forward-looking, anticipating how their decisions affect future rewards. Using data collected from YouTube, we show that content contribution is …
Visualizing Media Bias Through Twitter, Jisun An, Meeyoung Cha, Gummadi, Krishna, Jon Crowcroft, Daniele Queria
Visualizing Media Bias Through Twitter, Jisun An, Meeyoung Cha, Gummadi, Krishna, Jon Crowcroft, Daniele Queria
Research Collection School Of Computing and Information Systems
Traditional media outlets are known to report political news in a biased way, potentially affecting the political beliefs of the audience and even altering their voting behaviors. Therefore, tracking bias in everyday news and building a platform where people can receive balanced news information is important. We propose a model that maps the news media sources along a dimensional dichotomous political spectrum using the co-subscriptions relationships inferred by Twitter links. By analyzing 7 million follow links, we show that the political dichotomy naturally arises on Twitter when we only consider direct media subscription. Furthermore, we demonstrate a real-time Twitter-based application …
Context-Based Friend Suggestion In Online Photo-Sharing Community, Ting Yao, Chong-Wah Ngo, Tao Mei
Context-Based Friend Suggestion In Online Photo-Sharing Community, Ting Yao, Chong-Wah Ngo, Tao Mei
Research Collection School Of Computing and Information Systems
With the popularity of social media, web users tend to spend more time than before for sharing their experience and interest in online photo-sharing sites. The wide variety of sharing behaviors generate different metadata which pose new opportunities for the discovery of communities. We propose a new approach, named context-based friend suggestion, to leverage the diverse form of contextual cues for more effective friend suggestion in the social media community. Different from existing approaches, we consider both visual and geographical cues, and develop two user-based similarity measurements, i.e., visual similarity and geo similarity for characterizing user relationship. The problem of …
Sire: A Social Image Retrieval Engine, Steven C. H. Hoi, Pengcheng Wu
Sire: A Social Image Retrieval Engine, Steven C. H. Hoi, Pengcheng Wu
Research Collection School Of Computing and Information Systems
With the explosive growth of social media applications on the internet, billions of social images have been made available in many social media web sites nowadays. This has presented an open challenge of web-scale social image search. Unlike existing commercial web search engines that often adopt text based retrieval, in this demo, we present a novel web-based multimodal paradigm for large-scale social image retrieval, termed "Social Image Retrieval Engine" (SIRE), which effectively exploits both textual and visual contents to narrow down the semantic gap between high-level concepts and low-level visual features. A relevance feedback mechanism is also equipped to learn …
Content Contribution Under Revenue Sharing And Reputation Concern In Social Media: The Case Of Youtube, Qian Tang, Bin Gu, Andrew B. Whinston
Content Contribution Under Revenue Sharing And Reputation Concern In Social Media: The Case Of Youtube, Qian Tang, Bin Gu, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
A key feature of social media is that it allows individuals and businesses to contribute contents for public viewing. However, little is known about how content providers derive payoffs from such activities. In this study, we build a dynamic structural model to recover the utility function for content providers. Our model distinguishes short-term payoffs based on ad revenue sharing from long-term payoffs driven by content providers’ reputation. The model was estimated using a panel data of 914 top 1000 providers and 381 randomly selected providers on YouTube from Jun 7th, 2010, to Aug 7th, 2011. The two different sets of …
Smart Media: Bridging Interactions And Services For The Smart Internet, Margaret-Anne Storey, Lars Grammel, Christoph Treude
Smart Media: Bridging Interactions And Services For The Smart Internet, Margaret-Anne Storey, Lars Grammel, Christoph Treude
Research Collection School Of Computing and Information Systems
This chapter describes a need for Smart Media to enhance the vision of the Smart Internet. Smart Media is introduced as a mechanism to bridge Smart Services and Smart Interactions. Smart Media extends the existing notions of Media in HCI such as Hypermedia, New Media, Adaptive Hypermedia, and Social Media. There are three main contributions from this paper: (1) A historical perspective of media in HCI and how media could benefit from smartness; (2) through some high level sample scenarios, a proposal for Smart Media to meet the vision of the Smart Internet; and (3) a detailed example of how …