Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Computer Sciences (240)
- Physical Sciences and Mathematics (240)
- Databases and Information Systems (186)
- Numerical Analysis and Scientific Computing (78)
- Business (16)
-
- Engineering (13)
- Artificial Intelligence and Robotics (12)
- Computer Engineering (12)
- Software Engineering (12)
- Asian Studies (9)
- Graphics and Human Computer Interfaces (9)
- International and Area Studies (9)
- Digital Communications and Networking (8)
- Communication Technology and New Media (7)
- E-Commerce (7)
- Social Influence and Political Communication (5)
- Theory and Algorithms (5)
- Arts and Humanities (4)
- Music (4)
- Medicine and Health Sciences (3)
- Data Storage Systems (2)
- Finance and Financial Management (2)
- Information Security (2)
- OS and Networks (2)
- Public Health (2)
- Advertising and Promotion Management (1)
- Applied Behavior Analysis (1)
- Keyword
-
- Social media (58)
- Twitter (39)
- Sentiment analysis (9)
- Social Media (9)
- Social networks (8)
-
- Machine learning (7)
- Facebook (6)
- Microblogging (6)
- Social network (6)
- Data mining (5)
- Singapore (5)
- Analytics (4)
- Demographics (4)
- Homophily (4)
- User engagement (4)
- Customer service (3)
- Fake news (3)
- Instagram (3)
- Learning to rank (3)
- Machine Learning (3)
- Microblog (3)
- Multi-task learning (3)
- Opinion mining (3)
- Topic model (3)
- Topic modeling (3)
- Tweet geolocation (3)
- User behavior (3)
- Advertising (2)
- Audience segmentation (2)
- Autism (2)
Articles 211 - 240 of 249
Full-Text Articles in Social Media
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 …
Us Presidential Election 2012 Prediction Using Census Corrected Twitter Model, Junyu Choy, Michelle L. F. Cheong, Nang Laik Ma, Ping Shung Koo
Us Presidential Election 2012 Prediction Using Census Corrected Twitter Model, Junyu Choy, Michelle L. F. Cheong, Nang Laik Ma, Ping Shung Koo
Research Collection School Of Computing and Information Systems
US Presidential Election 2012 has been a very tight race between the two key candidates. Therewere intense battle between the two key candidates. The election reflects the sentiment of theelectorate towards the achievements of the incumbent President Obama. The campaign lastedseveral months and the effects can be felt in the internet and twitter. The presidential debatesinjected new vigor in the challenger's campaign and successfully captured the electorate of severalstates posing a threat to the incumbent's position. Much of the sentiment in the election has beencaptured in the online discussions. In this paper, we will be using the original model described …
A Probabilistic Graphical Model For Topic And Preference Discovery On Social Media, Lu Liu, Feida Zhu, Lei Zhang, Shiqiang Yang
A Probabilistic Graphical Model For Topic And Preference Discovery On Social Media, Lu Liu, Feida Zhu, Lei Zhang, Shiqiang Yang
Research Collection School Of Computing and Information Systems
Many web applications today thrive on offering services for large-scale multimedia data, e.g., Flickr for photos and YouTube for videos. However, these data, while rich in content, are usually sparse in textual descriptive information. For example, a video clip is often associated with only a few tags. Moreover, the textual descriptions are often overly specific to the video content. Such characteristics make it very challenging to discover topics at a satisfactory granularity on this kind of data. In this paper, we propose a generative probabilistic model named Preference-Topic Model (PTM) to introduce the dimension of user preferences to enhance the …
Influentials, Novelty, And Social Contagion: The Viral Power Of Average Friends, Close Communities, And Old News, Nicholas Harrigan, Palakorn Achananuparp, Ee Peng Lim
Influentials, Novelty, And Social Contagion: The Viral Power Of Average Friends, Close Communities, And Old News, Nicholas Harrigan, Palakorn Achananuparp, Ee Peng Lim
Research Collection School Of Computing and Information Systems
What is the effect of (1) popular individuals, and (2) community structures on the retransmission of socially contagious behavior? We examine a community of Twitter users over a five month period, operationalizing social contagion as ‘retweeting’, and social structure as the count of subgraphs (small patterns of ties and nodes) between users in the follower/following network. We find that popular individuals act as ‘inefficient hubs’ for social contagion: they have limited attention, are overloaded with inputs, and therefore display limited responsiveness to viral messages. We argue this contradicts the ‘law of the few’ and ‘influentials hypothesis’. We find that community …
(Hidden) Social Influences In Switching Mobile Service Platforms, Virpi K. Tuunainen, Tuure Tuunanen, Fiona Fui-Hoon Nah
(Hidden) Social Influences In Switching Mobile Service Platforms, Virpi K. Tuunainen, Tuure Tuunanen, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
During the past few years, the mobile industry has gone through a radical change from business focusing on excellence in device manufacturing and supply chain management to ecosystems around successful focal players, such as Apple and Google, controlling these service platforms. In order to compete in this environment, these firms need to understand what makes a consumer switch between these mobile service platforms. To that end, we conducted an inductive qualitative study with university students from Finland and USA as subjects (142 altogether), delving into how and why consumers switch mobile phones, and what are the factors affecting their decisions. …
Topic Discovery From Tweet Replies, Bingtian Dai, Ee Peng Lim, Philips Kokoh Prasetyo
Topic Discovery From Tweet Replies, Bingtian Dai, Ee Peng Lim, Philips Kokoh Prasetyo
Research Collection School Of Computing and Information Systems
Twitter is a popular online social information network service which allows people to read and post messages up to 140 characters, known as “tweets”. In this paper, we focus on the tweets between pairs of individuals, i.e., the tweet replies, and propose a generative model to discover topics among groups of twitter users. Our model has then been evaluated with a tweet dataset to show its effectiveness.
Finding Bursty Topics From Microblogs, Qiming Diao, Jing Jiang, Feida Zhu, Ee Peng Lim
Finding Bursty Topics From Microblogs, Qiming Diao, Jing Jiang, Feida Zhu, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Microblogs such as Twitter reflect the general public’s reactions to major events. Bursty topics from microblogs reveal what events have attracted the most online attention. Although bursty event detection from text streams has been studied before, previous work may not be suitable for microblogs because compared with other text streams such as news articles and scientific publications, microblog posts are particularly diverse and noisy. To find topics that have bursty patterns on microblogs, we propose a topic model that simultaneousy captures two observations: (1) posts published around the same time are more likely to have the same topic, and (2) …
Detecting Anomalous Twitter Users By Extreme Group Behaviors, Hanbo Dai, Ee-Peng Lim, Feida Zhu, Hwee Hwa Pang
Detecting Anomalous Twitter Users By Extreme Group Behaviors, Hanbo Dai, Ee-Peng Lim, Feida Zhu, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
Twitter has enjoyed tremendous popularity in the recent years. To help categorizing and search tweets, Twitter users assign hashtags to their tweets. Given that hashtag assignment is the primary way to semantically categorizing and search tweets, it is highly susceptible to abuse by spammers and other anomalous users [1]. Popular hashtags such as #Obama and #ladygaga could be hijacked by having them added to unrelated tweets with the intent of misleading many other users or promoting specific agenda to the users. The users performing this act are known as the hashtag hijackers. As the hijackers usually abuse common sets of …
When A Friend In Twitter Is A Friend In Life, Wei Xie, Cheng Li, Feida Zhu, Ee-Peng Lim, Xueqing Gong
When A Friend In Twitter Is A Friend In Life, Wei Xie, Cheng Li, Feida Zhu, Ee-Peng Lim, Xueqing Gong
Research Collection School Of Computing and Information Systems
Twitter is a fast-growing online social network service (SNS) where users can "follow" any other user to receive his or her mini-blogs which are called "tweets". In this paper, we study the problem of identifying a user's off-line real-life social community, which we call the user'sTwitter off-line community, purely from examining Twitter network structure. Based on observations from our user-verified Twitter data and results from previous works, we propose three principles about Twitter off-line communities. Incorporating these principles, we develop a novel algorithm to iteratively discover the Twitter off-line community based on a new way of measuring user closeness. According …
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 …
#Epicplay: Crowd-Sourcing Sports Video Highlights, Anthony Tang, Sebastian Boring
#Epicplay: Crowd-Sourcing Sports Video Highlights, Anthony Tang, Sebastian Boring
Research Collection School Of Computing and Information Systems
During a live sports event, many sports fans use social media as a part of their viewing experience, reporting on their thoughts on the event as it unfolds. In this work, we use this information stream to semantically annotate live broadcast sports games, using these annotations to select video highlights from the game. We demonstrate that this approach can be used to select highlights specific for fans of each team, and that these clips reflect the emotions of a fan during a game. Further, we describe how these clips differ from those seen on nightly sportscasts.
Structural Analysis In Multi-Relational Social Networks, Bing Tian Dai, Freddy Chong Tat Chua, Ee-Peng Lim
Structural Analysis In Multi-Relational Social Networks, Bing Tian Dai, Freddy Chong Tat Chua, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Modern social networks often consist of multiple relationsamong individuals. Understanding the structureof such multi-relational network is essential. In sociology,one way of structural analysis is to identify differentpositions and roles using blockmodels. In thispaper, we generalize stochastic blockmodels to GeneralizedStochastic Blockmodels (GSBM) for performing positionaland role analysis on multi-relational networks.Our GSBM generalizes many different kinds of MultivariateProbability Distribution Function (MVPDF) tomodel different kinds of multi-relational networks. Inparticular, we propose to use multivariate Poisson distributionfor multi-relational social networks. Our experimentsshow that GSBM is able to identify the structuresfor both synthetic and real world network data.These structures can further be used for predicting …
Manipulation Of Online Reviews: An Analysis Of Ratings, Readability, And Sentiments, Nan Hu, Indranil Bose, Noi Sian Koh, Ling Liu
Manipulation Of Online Reviews: An Analysis Of Ratings, Readability, And Sentiments, Nan Hu, Indranil Bose, Noi Sian Koh, Ling Liu
Research Collection School Of Computing and Information Systems
As consumers become increasingly reliant on online reviews to make purchase decisions, the sales of the product becomes dependent on the word of mouth (WOM) that it generates. As a result, there can be attempts by firms to manipulate online reviews of products to increase their sales. Despite the suspicion on the existence of such manipulation, the amount of such manipulation is unknown, and deciding which reviews to believe in is largely based on the reader's discretion and intuition. Therefore, the success of the manipulation of reviews by firms in generating sales of products is unknown. In this paper, we …
Modeling Social Strength In Social Media Community Via Kernel-Based Learning, Jinfeng Zhuang, Tao Mei, Steven C. H. Hoi, Xian-Sheng Hua, Shipeng Li
Modeling Social Strength In Social Media Community Via Kernel-Based Learning, Jinfeng Zhuang, Tao Mei, Steven C. H. Hoi, Xian-Sheng Hua, Shipeng Li
Research Collection School Of Computing and Information Systems
Modeling continuous social strength rather than conventional binary social ties in the social network can lead to a more precise and informative description of social relationship among people. In this paper, we study the problem of social strength modeling (SSM) for the users in a social media community, who are typically associated with diverse form of data. In particular, we take Flickr---the most popular online photo sharing community---as an example, in which users are sharing their experiences through substantial amounts of multimodal contents (e.g., photos, tags, geo-locations, friend lists) and social behaviors (e.g., commenting and joining interest groups). Such heterogeneous …
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 …
Wsm 2011: Third Acm Workshop On Social Media, Steven C. H. Hoi, Michal Jacovi, Ioannis Kompatsiaris, Jiebo Luo, Konstantinos Tserpes
Wsm 2011: Third Acm Workshop On Social Media, Steven C. H. Hoi, Michal Jacovi, Ioannis Kompatsiaris, Jiebo Luo, Konstantinos Tserpes
Research Collection School Of Computing and Information Systems
The Third Workshop on Social Media (WSM2011) continues the series of Workshops on Social Media in 2009 and 2010 and has been established as a platform for the presentation and discussion of the latest, key research issues in social media analysis, exploration, search, mining, and emerging new social media applications. It is held in conjunction with the ACM International Multimedia Conference (MM'11) at Scottsdale, Arizona, USA, 2011 and has attracted contributions on various aspects of social media including data mining from social media, content organization, geo-localization, personalization, recommendation systems, user experience, machine learning and social media approaches and architectures for …
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 …
Exploring Tweets Normalization And Query Time Sensitivity For Twitter Search, Zhongyu Wei, Wei Gao, Lanjun Zhou, Binyang Li, Kam-Fai Wong
Exploring Tweets Normalization And Query Time Sensitivity For Twitter Search, Zhongyu Wei, Wei Gao, Lanjun Zhou, Binyang Li, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
This paper presents our work for the Realtime Adhoc Task of TREC 2011 Microblog Track. Microblog texts like tweets are generally characterized by the inclusion of a large proportion of irregular expressions, such as ill-formed words, which can lead to significant mismatch between query terms and tweets. In addition, Twitter queries are distinguished from Web queries with many unique characteristics, one of which reflects the clearly distinct temporal aspects of Twitter search behavior. In this study, we deal with the first problem by normalizing tweet texts and the second by capturing the temporal characteristics of topic. We divided topics into …
Mining Direct Antagonistic Communities In Explicit Trust Networks, David Lo, Didi Surian, Zhang Kuan, Ee Peng Lim
Mining Direct Antagonistic Communities In Explicit Trust Networks, David Lo, Didi Surian, Zhang Kuan, Ee Peng Lim
Research Collection School Of Computing and Information Systems
There has been a recent increase of interest in analyzing trust and friendship networks to gain insights about relationship dynamics among users. Many sites such as Epinions, Facebook, and other social networking sites allow users to declare trusts or friendships between different members of the community. In this work, we are interested in extracting direct antagonistic communities (DACs) within a rich trust network involving trusts and distrusts. Each DAC is formed by two subcommunities with trust relationships among members of each sub-community but distrust relationships across the sub-communities. We develop an efficient algorithm that could analyze large trust networks leveraging …
On Modeling Virality Of Twitter Content, Tuan Anh Hoang, Ee Peng Lim, Palakorn Achananuparp, Jing Jiang, Feida Zhu
On Modeling Virality Of Twitter Content, Tuan Anh Hoang, Ee Peng Lim, Palakorn Achananuparp, Jing Jiang, Feida Zhu
Research Collection School Of Computing and Information Systems
Twitter is a popular microblogging site where users can easily use mobile phones or desktop machines to generate short messages to be shared with others in realtime. Twitter has seen heavy usage in many recent international events including Japan earthquake, Iran election, etc. In such events, many tweets may become viral for different reasons. In this paper, we study the virality of socio-political tweet content in the Singapore’s 2011 general election (GE2011). We collected tweet data generated by about 20K Singapore users from 1 April 2011 till 12 May 2011, and the follow relationships among them. We introduce several quantitative …
Virality Modeling And Analysis, Tuan Anh Hoang, Ee-Peng Lim
Virality Modeling And Analysis, Tuan Anh Hoang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Virality is a virus-like behavior that allows a piece of information to widely and quickly diffuse within the network of adopters through word of mouth. It is about how easy users propagate information to their friends and friends of friends by means of diffusion. While virality of information has several interesting applications, there are much research to be conducted on virality. These areas of research include understanding the mechanism of virality, modeling the virality both qualitatively and quantitatively, and applying virality to applications such as marketing, event detection, and others. In this paper, we survey existing works on quantitative models …
A Survey Of Information Diffusion Models And Relevant Problems, Minh Duc Luu, Tuan Anh Hoang, Ee-Peng Lim
A Survey Of Information Diffusion Models And Relevant Problems, Minh Duc Luu, Tuan Anh Hoang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
There has been tremendous interest in diffusion of innovations or information in a social system. Nowadays, social networks (offline as well as online) are considered as important medium for diffusion and large amount of research has been conducted to understand the dynamics of diffusion in social networks. In this work, we review some of the models proposed for diffusion in social networks. We also highlight the major features of these models by dividing the surveyed models into two categories: non-network and network diffusion models. The former refers to user communities without any knowledge about the user relationship network and the …
Media Landscape In Twitter: A World Of New Conventions And Political Diversity, Jisun An, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft
Media Landscape In Twitter: A World Of New Conventions And Political Diversity, Jisun An, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft
Research Collection School Of Computing and Information Systems
We present a preliminary but groundbreaking study of the media landscape of Twitter. We use public data on whom follows who to uncover common behaviour in media consumption, the relationship between various classes of media, and the diversity of media content which social links may bring. Our analysis shows that there is a non-negligible amount of indirect media exposure, either through friends who follow particular media sources, or via retweeted messages. We show that the indirect media exposure expands the political diversity of news to which users are exposed to a surprising extent, increasing the range by between 60-98%. These …
Topical Keyphrase Extraction From Twitter, Xin Zhao, Jing Jiang, Jing He, Yang Song, Palakorn Achananuparp, Ee Peng Lim, Xiaoming Li
Topical Keyphrase Extraction From Twitter, Xin Zhao, Jing Jiang, Jing He, Yang Song, Palakorn Achananuparp, Ee Peng Lim, Xiaoming Li
Research Collection School Of Computing and Information Systems
Summarizing and analyzing Twitter content is an important and challenging task. In this paper, we propose to extract topical keyphrases as one way to summarize Twitter. We propose a context-sensitive topical PageRank method for keyword ranking and a probabilistic scoring function that considers both relevance and interestingness of keyphrases for keyphrase ranking. We evaluate our proposed methods on a large Twitter data set. Experiments show that these methods are very effective for topical keyphrase extraction.
Comparing Twitter And Traditional Media Using Topic Models, Wayne Xin Zhao, Jing Jiang, Jianshu Weng, Jing He, Ee Peng Lim, Hongfei Yan, Xiaoming Li
Comparing Twitter And Traditional Media Using Topic Models, Wayne Xin Zhao, Jing Jiang, Jianshu Weng, Jing He, Ee Peng Lim, Hongfei Yan, Xiaoming Li
Research Collection School Of Computing and Information Systems
Twitter as a new form of social media can potentially contain much useful information, but content analysis on Twitter has not been well studied. In particular, it is not clear whether as an information source Twitter can be simply regarded as a faster news feed that covers mostly the same information as traditional news media. In This paper we empirically compare the content of Twitter with a traditional news medium, New York Times, using unsupervised topic modeling. We use a Twitter-LDA model to discover topics from a representative sample of the entire Twitter. We then use text mining techniques to …
Utility-Oriented K-Anonymization On Social Networks, Yazhe Wang, Long Xie, Baihua Zheng, Ken C. K. Lee
Utility-Oriented K-Anonymization On Social Networks, Yazhe Wang, Long Xie, Baihua Zheng, Ken C. K. Lee
Research Collection School Of Computing and Information Systems
"Identity disclosure" problem on publishing social network data has gained intensive focus from academia. Existing k-anonymization algorithms on social network may result in nontrivial utility loss. The reason is that the number of the edges modified when anonymizing the social network is the only metric to evaluate utility loss, not considering the fact that different edge modifications have different impact on the network structure. To tackle this issue, we propose a novel utility-oriented social network anonymization scheme to achieve privacy protection with relatively low utility loss. First, a proper utility evaluation model is proposed. It focuses on the changes on …
Manipulation In Digital Word-Of-Mouth: A Reality Check For Book Reviews, Nan Hu, Indranil Bose, Yunjun Gao, Ling Liu
Manipulation In Digital Word-Of-Mouth: A Reality Check For Book Reviews, Nan Hu, Indranil Bose, Yunjun Gao, Ling Liu
Research Collection School Of Computing and Information Systems
Built upon the discretionary accrual-based earnings management framework, our paper develops a discretionary manipulation proxy to study the management of online reviews. We reveal that fraudulent review manipulation is a serious problem for 1) non-bestseller books; 2) books whose reviews are classified as not very helpful; 3) books that experience greater variability in the helpfulness of their online reviews; and 4) popular books as well as high-priced books. We also show that review management decreases with the passage of time. Just like fraudulent earnings management, manipulated online reviews reflect inauthentic information from which consumers might derive wrong valuation especially for …
The Impact Of Social Media On Software Engineering Practices And Tools, Margaret-Anne Storey, Christoph Treude, Arie Van Deursen, Li-Te Cheng
The Impact Of Social Media On Software Engineering Practices And Tools, Margaret-Anne Storey, Christoph Treude, Arie Van Deursen, Li-Te Cheng
Research Collection School Of Computing and Information Systems
Today's generation of software developers frequently make use of social media, either as an adjunct or integrated into a wide range of tools ranging from code editors and issue trackers, to IDEs and web-based portals. The role of social media usage in software engineering is not well understood, and yet the use of these mechanisms influences software development practices. In this position paper, we advocate for research that strives to understand the benefits, risks and limitations of using social media in software development at the team, project and community levels. Guided by the implications of current tools and social media …
Wsm'10: Second Acm Workshop On Social Media, Susanne Boll, Steven C. H. Hoi, Roelof Van Zwol, Jiebo Luo
Wsm'10: Second Acm Workshop On Social Media, Susanne Boll, Steven C. H. Hoi, Roelof Van Zwol, Jiebo Luo
Research Collection School Of Computing and Information Systems
The ACM SIGMM International Workshop on Social Media (WSM'10) is the second workshop held in conjunction with the ACM International Multimedia Conference (MM'10) at Firenze, Italy, 2010. This workshop provides a forum for researchers and practitioners from all over the world to share information on their latest investigations on social media analysis, exploration, search, mining, and emerging new social media applications.
Mining Interesting Link Formation Rules In Social Networks, Cane Wing-Ki Leung, Ee Peng Lim, David Lo, Jianshu Weng
Mining Interesting Link Formation Rules In Social Networks, Cane Wing-Ki Leung, Ee Peng Lim, David Lo, Jianshu Weng
Research Collection School Of Computing and Information Systems
Link structures are important patterns one looks out for when modeling and analyzing social networks. In this paper, we propose the task of mining interesting Link Formation rules (LF-rules) containing link structures known as Link Formation patterns (LF-patterns). LF-patterns capture various dyadic and/or triadic structures among groups of nodes, while LF-rules capture the formation of a new link from a focal node to another node as a postcondition of existing connections between the two nodes. We devise a novel LF-rule mining algorithm, known as LFR-Miner, based on frequent subgraph mining for our task. In addition to using a support-confidence framework …