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- Keyword
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- Social media (3)
- Twitter (3)
- Data Mining and Knowledge Discovery (2)
- Facebook (2)
- Model (2)
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- Transportation network (2)
- Artificial Intelligence (1)
- Bursty events (1)
- Bursty topic (1)
- Collaborative Filtering (1)
- Complex Networks (1)
- Computer Application in Social and Behavioral Sciences (1)
- Computer Communication Networks (1)
- Data mining (1)
- Database applications (1)
- Database management (1)
- Direct antagonistic community (1)
- Discussion forum posts (1)
- Dormant tie (1)
- ESDA (1)
- Enterprise GIS (1)
- Entity search (1)
- Event detection (1)
- Event identification (1)
- Friend suggestion (1)
- GIS (1)
- GWR (1)
- Gamification (1)
- Gaussian mixture (1)
- GeoVisual Analytics (1)
Articles 1 - 30 of 31
Full-Text Articles in Databases and Information Systems
Two Formulas For Success In Social Media: Social Learning And Network Effects, Liangfei Qiu, Qian Tang, Andrew B. Whinston
Two Formulas For Success In Social Media: Social Learning And Network Effects, Liangfei Qiu, Qian Tang, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
This paper examines social learning and network effects that are particularly important for online videos, considering the limited marketing campaigns of user-generated content. Rather than combining both social learning and network effects under the umbrella of social contagion or peer influence, we develop a theoretical model and empirically identify social learning and network effects separately. Using a unique data set from YouTube, we find that both mechanisms have statistically and economically significant effects on video views, and which mechanism dominates depends on the specific video type.
Topicsketch: Real-Time Bursty Topic Detection From Twitter, Wei Xie, Feida Zhu, Jing Jiang, Ee Peng Lim, Ke Wang
Topicsketch: Real-Time Bursty Topic Detection From Twitter, Wei Xie, Feida Zhu, Jing Jiang, Ee Peng Lim, Ke Wang
Research Collection School Of Computing and Information Systems
Twitter has become one of the largest platforms for users around the world to share anything happening around them with friends and beyond. A bursty topic in Twitter is one that triggers a surge of relevant tweets within a short time, which often reflects important events of mass interest. How to leverage Twitter for early detection of bursty topics has therefore become an important research problem with immense practical value. Despite the wealth of research work on topic modeling and analysis in Twitter, it remains a huge challenge to detect bursty topics in real-time. As existing methods can hardly scale …
Predicting User's Political Party Using Ideological Stances, Swapna Gottopati, Minghui Qiu, Liu Yang, Feida Zhu, Jing Jiang
Predicting User's Political Party Using Ideological Stances, Swapna Gottopati, Minghui Qiu, Liu Yang, Feida Zhu, Jing Jiang
Research Collection School Of Computing and Information Systems
Predicting users political party in social media has important impacts on many real world applications such as targeted advertising, recommendation and personalization. Several political research studies on it indicate that political parties’ ideological beliefs on sociopolitical issues may influence the users political leaning. In our work, we exploit users’ ideological stances on controversial issues to predict political party of online users. We propose a collaborative filtering approach to solve the data sparsity problem of users stances on ideological topics and apply clustering method to group the users with the same party. We evaluated several state-of-the-art methods for party prediction task …
Why Do I Retweet It? An Information Propagation Model For Microblogs, Fabio Pezzoni, Jisun An, Andrea Passarella, Jon Crowcroft, Marco Conti
Why Do I Retweet It? An Information Propagation Model For Microblogs, Fabio Pezzoni, Jisun An, Andrea Passarella, Jon Crowcroft, Marco Conti
Research Collection School Of Computing and Information Systems
Microblogging platforms are Web 2.0 services that represent a suitable environment for studying how information is propagated in social networks and how users can become influential. In this work we analyse the impact of the network features and of the users' behaviour on the information diffusion. Our analysis highlights a strong relation between the level of visibility of a message in the flow of information seen by a user and the probability that the user further disseminates the message. In addition, we also highlight the existence of other latent factors that impact on the dissemination probability, correlated with the properties …
Social Sensing For Urban Crisis Management: The Case Of Singapore Haze, Philips Kokoh Prasetyo, Ming Gao, Ee Peng Lim, Christie N. Scollon
Social Sensing For Urban Crisis Management: The Case Of Singapore Haze, Philips Kokoh Prasetyo, Ming Gao, Ee Peng Lim, Christie N. Scollon
Research Collection School Of Computing and Information Systems
Sensing social media for trends and events has become possible as increasing number of users rely on social media to share information. In the event of a major disaster or social event, one can therefore study the event quickly by gathering and analyzing social media data. One can also design appropriate responses such as allocating resources to the affected areas, sharing event related information, and managing public anxiety. Past research on social event studies using social media often focused on one type of data analysis (e.g., hashtag clusters, diffusion of events, influential users, etc.) on a single social media data …
Information Vs Interaction: An Alternative User Ranking Model For Social Networks, Wei Xie, Ai Phuong Hoang, Feida Zhu, Ee Peng Lim
Information Vs Interaction: An Alternative User Ranking Model For Social Networks, Wei Xie, Ai Phuong Hoang, Feida Zhu, Ee Peng Lim
Research Collection School Of Computing and Information Systems
The recent years have seen an unprecedented boom of social network services, such as Twitter, which boasts over 200 million users. In such big social platforms, the influential users are ideal targets for viral marketing to potentially reach an audience of maximal size. Most proposed algorithms rely on the linkage structure of the respective underlying network to determine the information flow and hence indicate a users influence. From social interaction perspective, we built a model based on the dynamic user interactions constantly taking place on top of these linkage structures. In particular, in the Twitter setting we supposed a principle …
Predicting Best Answerers For New Questions: An Approach Leveraging Topic Modeling And Collaborative Voting, Yuan Tian, Pavneet Singh Kochhar, Ee Peng Lim, Feida Zhu, David Lo
Predicting Best Answerers For New Questions: An Approach Leveraging Topic Modeling And Collaborative Voting, Yuan Tian, Pavneet Singh Kochhar, Ee Peng Lim, Feida Zhu, David Lo
Research Collection School Of Computing and Information Systems
Community Question Answering (CQA) sites are becoming increasingly important source of information where users can share knowledge on various topics. Although these platforms bring new opportunities for users to seek help or provide solutions, they also pose many challenges with the ever growing size of the community. The sheer number of questions posted everyday motivates the problem of routing questions to the appropriate users who can answer them. In this paper, we propose an approach to predict the best answerer for a new question on CQA site. Our approach considers both user interest and user expertise relevant to the topics …
Social Listening For Customer Acquisition, Juan Du, Biying Tan, Feida Zhu, Ee-Peng Lim
Social Listening For Customer Acquisition, Juan Du, Biying Tan, Feida Zhu, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Social network analysis has received much attention from corporations recently. Corporations are trying to utilize social media platforms such as Twitter, Facebook and Sina Weibo to expand their own markets. Our system is an online tool to assist these corporations to 1) find potential customers, and 2) track a list of users by specific events from social networks. We employ both textual and network information, and thus produce a keyword-based relevance score for each user in pre-defined dimensions, which indicates the probability of the adoption of a product. Based on the score and its trend, out tool is able to …
Merged Aggregate Nearest Neighbor Query Processing In Road Networks, Weiwei Sun, Chong Chen, Baihua Zheng, Chunan Chen, Liang Zhu
Merged Aggregate Nearest Neighbor Query Processing In Road Networks, Weiwei Sun, Chong Chen, Baihua Zheng, Chunan Chen, Liang Zhu
Research Collection School Of Computing and Information Systems
Aggregate nearest neighbor query, which returns a common interesting point that minimizes the aggregate distance for a given query point set, is one of the most important operations in spatial databases and their application domains. This paper addresses the problem of finding the aggregate nearest neighbor for a merged set that consists of the given query point set and multiple points needed to be selected from a candidate set, which we name as merged aggregate nearest neighbor(MANN) query. This paper proposes an effective algorithm to process MANN query in road networks based on our pruning strategies. Extensive experiments are conducted …
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 …
The Myths Of G-Tech For Business Decision Making, Tin Seong Kam
The Myths Of G-Tech For Business Decision Making, Tin Seong Kam
Research Collection School Of Computing and Information Systems
More than 80% of organisation data are location related - the locations where transactions are done, where retailers are found, and of customers who buy their products. Since the early 2005, there has been an increasing interest among the business community to use geospatial technology to enhance decision making process at both strategic and operational levels. Millions of dollars and man-hours have been invested into driving their geo-technology development and implementation. The use of geospatial technology in business, however, tends to confine to simple mapping. Many of these failures are the victims of misperception. Some of the perpetrators are practitioners. …
Riga: A Rich Internet Geospatial Analytics Application For Area-Based Data, Tin Seong Kam
Riga: A Rich Internet Geospatial Analytics Application For Area-Based Data, Tin Seong Kam
Research Collection School Of Computing and Information Systems
In this information age, more and more public statistical data such as population census, household living, local economy and business establishment are distributed over the internet within the framework of spatial data infrastructure. By and large, these data are organized geographically such as region, province as well as district. Usually, they are published in the form of digital maps over the internet as simple points, lines and polygons markers limited or no analytical function available to transform these data into useful information. To meet the analytical needs of casual public data users, we contribute RIGA, a rich internet geospatial analytics …
Generative Models For Item Adoptions Using Social Correlation, Freddy Chong Tat Chua, Hady Wirawan Lauw, Ee Peng Lim
Generative Models For Item Adoptions Using Social Correlation, Freddy Chong Tat Chua, Hady Wirawan Lauw, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Users face many choices on the Web when it comes to choosing which product to buy, which video to watch, etc. In making adoption decisions, users rely not only on their own preferences, but also on friends. We call the latter social correlation which may be caused by the homophily and social influence effects. In this paper, we focus on modeling social correlation on users’ item adoptions. Given a user-user social graph and an item-user adoption graph, our research seeks to answer the following questions: whether the items adopted by a user correlate to items adopted by her friends, and …
Politics, Sharing And Emotion In Microblogs, Tuan-Anh Hoang, William Cohen, Ee Peng Lim, Doug Pierce, David Redlawsk
Politics, Sharing And Emotion In Microblogs, Tuan-Anh Hoang, William Cohen, Ee Peng Lim, Doug Pierce, David Redlawsk
Research Collection School Of Computing and Information Systems
In political contexts, it is known that people act as "motivated reasoners", i.e., information is evaluated first for emotional affect, and this emotional reaction influences later deliberative reasoning steps. As social media becomes a more and more prevalent way of receiving political information, it becomes important to understand more completely the interaction between information, emotion, social community, and information-sharing behavior. In this paper, we describe a high-precision classifier for politically-oriented tweets, and an accurate classifier of a Twitter user's political affiliation. Coupled with existing sentiment-analysis tools for microblogs, these methods enable us to systematically study the interaction of emotion and …
Delayflow Centrality For Identifying Critical Nodes In Transportation Networks, Yew-Yih Cheng, Roy Ka Wei Lee, Ee-Peng Lim, Feida Zhu
Delayflow Centrality For Identifying Critical Nodes In Transportation Networks, Yew-Yih Cheng, Roy Ka Wei Lee, Ee-Peng Lim, Feida Zhu
Research Collection School Of Computing and Information Systems
In an urban city, its transportation network supports efficient flow of people between different parts of the city. Failures in the network can cause major disruptions to commuter and business activities which can result in both significant economic and time losses. In this paper, we investigate the use of centrality measures to determine critical nodes in a transportation network so as to improve the design of the network as well as to devise plans for coping with network failures. Most centrality measures in social network analysis research unfortunately consider only topological structure of the network and are oblivious of transportation …
Best Upgrade Plans For Large Road Networks, Yimin Lin, Kyriakos Mouratidis
Best Upgrade Plans For Large Road Networks, Yimin Lin, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
In this paper, we consider a new problem in the context of road network databases, named Resource Constrained Best Upgrade Plan computation (BUP, for short). Consider a transportation network (weighted graph) G where a subset of the edges are upgradable, i.e., for each such edge there is a cost, which if spent, the weight of the edge can be reduced to a specific new value. Given a source and a destination in G, and a budget (resource constraint) B, the BUP problem is to identify which upgradable edges should be upgraded so that the shortest path distance between source and …
Reviving Dormant Ties In An Online Social Network Experiment, Ee Peng Lim, Denzil Correa, David Lo, Michael Finegold, Feida Zhu
Reviving Dormant Ties In An Online Social Network Experiment, Ee Peng Lim, Denzil Correa, David Lo, Michael Finegold, Feida Zhu
Research Collection School Of Computing and Information Systems
Social network users connect and interact with one another to fulfil different kinds of social and information needs. When interaction ceases between two users, we say that their tie becomes dormant. While there are different underlying reasons of dormant ties, it is important to find means to revive such ties so as to maintain vibrancy in the relationships. In this work, we thus focus on designing an online experiment to evaluate the effectiveness of personalized social messages to revive dormant ties. The experiment carefully selects users with dormant ties so that no user gets mixed treatments and be affected by …
Mining Direct Antagonistic Communities In Signed Social Networks, David Lo, Didi Surian, Philips Kokoh Prasetyo, Zhang Kuan, Ee Peng Lim
Mining Direct Antagonistic Communities In Signed Social Networks, David Lo, Didi Surian, Philips Kokoh Prasetyo, Zhang Kuan, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Social networks provide a wealth of data to study relationship dynamics among people. Most social networks such as Epinions and Facebook allow users to declare trusts or friendships with other users. Some of them also allow users to declare distrusts or negative relationships. When both positive and negative links co-exist in a network, some interesting community structures can be studied. In this work, we mine Direct Antagonistic Communities (DACs) within such signed networks. Each DAC consists of two sub-communities with positive relationships among members of each sub-community, and negative relationships among members of the other sub-community. Identifying direct antagonistic communities …
A Latent Variable Model For Viewpoint Discovery From Threaded Forum Posts, Minghui Qiu, Jing Jiang
A Latent Variable Model For Viewpoint Discovery From Threaded Forum Posts, Minghui Qiu, Jing Jiang
Research Collection School Of Computing and Information Systems
Threaded discussion forums provide an important social media platform. Its rich user generated content has served as an important source of public feedback. To automatically discover the viewpoints or stances on hot issues from forum threads is an important and useful task. In this paper, we propose a novel latent variable model for viewpoint discovery from threaded forum posts. Our model is a principled generative latent variable model which captures three important factors: viewpoint specific topic preference, user identity and user interactions. Evaluation results show that our model clearly outperforms a number of baseline models in terms of both clustering …
Real Time Event Detection In Twitter, Xun Wang, Feida Zhu, Jing Jiang, Sujian Li
Real Time Event Detection In Twitter, Xun Wang, Feida Zhu, Jing Jiang, Sujian Li
Research Collection School Of Computing and Information Systems
Event detection has been an important task for a long time. When it comes to Twitter, new problems are presented. Twitter data is a huge temporal data flow with much noise and various kinds of topics. Traditional sophisticated methods with a high computational complexity aren’t designed to handle such data flow efficiently. In this paper, we propose a mixture Gaussian model for bursty word extraction in Twitter and then employ a novel time-dependent HDP model for new topic detection. Our model can grasp new events, the location and the time an event becomes bursty promptly and accurately. Experiments show the …
Unified Entity Search In Social Media Community, Ting Yao, Yuan Liu, Chong-Wah Ngo, Tao Mei
Unified Entity Search In Social Media Community, Ting Yao, Yuan Liu, Chong-Wah Ngo, Tao Mei
Research Collection School Of Computing and Information Systems
The search for entities is the most common search behavior on the Web, especially in social media communities where entities (such as images, videos, people, locations, and tags) are highly heterogeneous and correlated. While previous research usually deals with these social media entities separately, we are investigating in this paper a unified, multilevel, and correlative entity graph to represent the unstructured social media data, through which various applications (e.g., friend suggestion, personalized image search, image tagging, etc.) can be realized more effectively in one single framework. We regard the social media objects equally as “entities” and all of these applications …
Impact Of Multimedia In Sina Weibo: Popularity And Life Span, Xun Zhao, Feida Zhu, Weining Qian, Aoying Zhou
Impact Of Multimedia In Sina Weibo: Popularity And Life Span, Xun Zhao, Feida Zhu, Weining Qian, Aoying Zhou
Research Collection School Of Computing and Information Systems
Multimedia contents such as images and videos are widely used in social network sites nowadays. Sina Weibo, a Chinese microblogging service, is one of the first microblog platforms to incorporate multimedia content sharing features. This work provides statistical analysis on how multimedia contents are produced, consumed, and propagated in Sina Weibo. Based on 230 million tweets and 1.8 million user profiles in Sina Weibo, we study the impact of multimedia contents on the popularity of both users and tweets as well as tweet life span. Our preliminary study shows that multimedia tweets dominant pure text ones in Sina Weibo. Multimedia …
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 …
Retweeting: An Act Of Viral Users, Susceptible Users, Or Viral Topics?, Tuan-Anh Hoang, Ee Peng Lim
Retweeting: An Act Of Viral Users, Susceptible Users, Or Viral Topics?, Tuan-Anh Hoang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
When a user retweets, there are three behavioral factors that cause the actions. They are the topic virality, user virality and user susceptibility. Topic virality captures the degree to which a topic attracts retweets by users. For each topic, user virality and susceptibility refer to the likelihood that a user attracts retweets and performs retweeting respectively. To model a set of observed retweet data as a result of these three topic specific factors, we first represent the retweets as a three-dimensional tensor of the tweet authors, their followers, and the tweets themselves. We then propose the V 2S model, a …
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 …
Twicube: A Real-Time Twitter Online Community Analysis Tool, Juan Du, Wei Xie, Cheng Li, Feida Zhu, Ee Peng Lim
Twicube: A Real-Time Twitter Online Community Analysis Tool, Juan Du, Wei Xie, Cheng Li, Feida Zhu, Ee Peng Lim
Research Collection School Of Computing and Information Systems
As a micro-blogging service, Twitter differs from other social network services in two ways: 1) the absence of mutual consent in establishing follow links and 2) being a mixture of news media and social network. A key question to ask in better understanding Twitter user behavior is which part of a user’s Twitter network reflects one’s real-life social network. TwiCube is an online tool that employs a novel algorithm capable of identifying a user’s real-life social community, which we call the user’s off-line community, purely from examining the link structure among the user’s followers and followees. Based on the identified …
Dynamic Label Propagation In Social Networks, Juan Du, Feida Zhu, Ee Peng Lim
Dynamic Label Propagation In Social Networks, Juan Du, Feida Zhu, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Label propagation has been studied for many years, starting from a set of nodes with labels and then propagating to those without labels. In social networks, building complete user profiles like interests and affiliations contributes to the systems like link prediction, personalized feeding, etc. Since the labels for each user are mostly not filled, we often employ some people to label these users. And therefore, the cost of human labeling is high if the data set is large. To reduce the expense, we need to select the optimal data set for labeling, which produces the best propagation result. In this …
Finding The Optimal Social Trust Path For The Selection Of Trustworthy Service Providers In Complex Social Networks, Guanfeng Liu, Yan Wang, Mehmet A. Orgun, Ee Peng Lim
Finding The Optimal Social Trust Path For The Selection Of Trustworthy Service Providers In Complex Social Networks, Guanfeng Liu, Yan Wang, Mehmet A. Orgun, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Online social networks have provided the infrastructure for a number of emerging applications in recent years, e.g., for the recommendation of service providers or the recommendation of files as services. In these applications, trust is one of the most important factors in decision making by a service consumer, requiring the evaluation of the trustworthiness of a service provider along the social trust paths from a service consumer to the service provider. However, there are usually many social trust paths between two participants who are unknown to one another. In addition, some social information, such as social relationships between participants and …
K-Pop Live: Social Networking & Language Learning Platform, Thomas Chua, Chin Leng Ong, Kian Ming Png, Aloysius Lau, Houston Toh, Feida Zhu, Kyong Jin Shim, Ee-Peng Lim
K-Pop Live: Social Networking & Language Learning Platform, Thomas Chua, Chin Leng Ong, Kian Ming Png, Aloysius Lau, Houston Toh, Feida Zhu, Kyong Jin Shim, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
K-Pop live is a social networking and language learning platform developed by an undergraduate student team from Singapore Management University. K-Pop live aims to combine social media together with gamification to promote Korean culture. It consolidates all relevant Tweets from Twitter as well as videos from YouTube. The platform allows the user to connect with his friends who share similar interests in terms of K-pop artists and music.
Hypergraph Index: An Index For Context-Aware Nearest Neighbor Query On Social Networks, Yazhe Wang, Baihua Zheng
Hypergraph Index: An Index For Context-Aware Nearest Neighbor Query On Social Networks, Yazhe Wang, Baihua Zheng
Research Collection School Of Computing and Information Systems
Social network has been touted as the No. 2 innovation in a recent IEEE Spectrum Special Report on “Top 11 Technologies of the Decade”, and it has cemented its status as a bona fide Internet phenomenon. With more and more people starting using social networks to share ideas, activities, events, and interests with other members within the network, social networks contain a huge amount of content. However, it might not be easy to navigate social networks to find specific information. In this paper, we define a new type of queries, namely context-aware nearest neighbor (CANN) search over social network to …