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Research Collection School Of Computing and Information Systems

2012

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Full-Text Articles in Databases and Information Systems

B-Cell Epitope Prediction Through A Graph Model, Liang Zhao, Limsoon Wong, Lanyuan Lu, Steven C. H. Hoi, Jinyan Li Dec 2012

B-Cell Epitope Prediction Through A Graph Model, Liang Zhao, Limsoon Wong, Lanyuan Lu, Steven C. H. Hoi, Jinyan Li

Research Collection School Of Computing and Information Systems

Prediction of B-cell epitopes from antigens is useful to understand the immune basis of antibody-antigen recognition, and is helpful in vaccine design and drug development. Tremendous efforts have been devoted to this long-studied problem, however, existing methods have at least two common limitations. One is that they only favor prediction of those epitopes with protrusive conformations, but show poor performance in dealing with planar epitopes. The other limit is that they predict all of the antigenic residues of an antigen as belonging to one single epitope even when multiple non-overlapping epitopes of an antigen exist.


Structural And Functional Analysis Of Multi-Interface Domains, Liang Zhao, Steven C. H. Hoi, Limsoon Wong, Tobias Hamp, Jinyan Li Dec 2012

Structural And Functional Analysis Of Multi-Interface Domains, Liang Zhao, Steven C. H. Hoi, Limsoon Wong, Tobias Hamp, Jinyan Li

Research Collection School Of Computing and Information Systems

A multi-interface domain is a domain that can shape multiple and distinctive binding sites to contact with many other domains, forming a hub in domain-domain interaction networks. The functions played by the multiple interfaces are usually different, but there is no strict bijection between the functions and interfaces as some subsets of the interfaces play the same function. This work applies graph theory and algorithms to discover fingerprints for the multiple interfaces of a domain and to establish associations between the interfaces and functions, based on a huge set of multi-interface proteins from PDB. We found that about 40% of …


A Survey Of Recommender Systems In Twitter, Su Mon Kywe, Ee Peng Lim, Feida Zhu Dec 2012

A Survey Of Recommender Systems In Twitter, Su Mon Kywe, Ee Peng Lim, Feida Zhu

Research Collection School Of Computing and Information Systems

Twitter is a social information network where short messages or tweets are shared among a large number of users through a very simple messaging mechanism. With a population of more than 100M users generating more than 300M tweets each day, Twitter users can be easily overwhelmed by the massive amount of information available and the huge number of people they can interact with. To overcome the above information overload problem, recommender systems can be introduced to help users make the appropriate selection. Researchers have began to study recommendation problems in Twitter but their works usually address individual recommendation tasks. There …


Cross-Lingual Identification Of Ambiguous Discourse Connectives For Resource-Poor Language, Lanjun Zhou, Wei Gao, Binyang Li, Zhongyu Wei, Kam-Fai Wong Dec 2012

Cross-Lingual Identification Of Ambiguous Discourse Connectives For Resource-Poor Language, Lanjun Zhou, Wei Gao, Binyang Li, Zhongyu Wei, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

The lack of annotated corpora brings limitations in research of discourse classification for many languages. In this paper, we present the first effort towards recognizing ambiguities of discourse connectives, which is fundamental to discourse classification for resource-poor language such as Chinese. A language independent framework is proposed utilizing bilingual dictionaries, Penn Discourse Treebank and parallel data between English and Chinese. We start from translating the English connectives to Chinese using a bi-lingual dictionary. Then, the ambiguities in terms of senses a connective may signal are estimated based on the ambiguities of English connectives and word alignment information. Finally, the ambiguity …


Cost-Sensitive Online Classification, Jialei Wang, Peilin Zhao, Steven C. H. Hoi Dec 2012

Cost-Sensitive Online Classification, Jialei Wang, Peilin Zhao, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Both cost-sensitive classification and online learning have been extensively studied in data mining and machine learning communities, respectively. However, very limited study addresses an important intersecting problem, that is, “Cost-Sensitive Online Classification". In this paper, we formally study this problem, and propose a new framework for Cost-Sensitive Online Classification by directly optimizing cost-sensitive measures using online gradient descent techniques. Specifically, we propose two novel cost-sensitive online classification algorithms, which are designed to directly optimize two well-known cost-sensitive measures: (i) maximization of weighted sum of sensitivity and specificity, and (ii) minimization of weighted misclassification cost. We analyze the theoretical bounds of …


On Recommending Hashtags In Twitter Networks, Su Mon Kywe, Tuan-Anh Hoang, Ee Peng Lim, Feida Zhu Dec 2012

On Recommending Hashtags In Twitter Networks, Su Mon Kywe, Tuan-Anh Hoang, Ee Peng Lim, Feida Zhu

Research Collection School Of Computing and Information Systems

Twitter network is currently overwhelmed by massive amount of tweets generated by its users. To effectively organize and search tweets, users have to depend on appropriate hashtags inserted into tweets. We begin our research on hashtags by first analyzing a Twitter dataset generated by more than 150,000 Singapore users over a three-month period. Among several interesting findings about hashtag usage by this user community, we have found a consistent and significant use of new hashtags on a daily basis. This suggests that most hashtags have very short life span. We further propose a novel hashtag recommendation method based on collaborative …


Extracting And Normalizing Entity-Actions From Users' Comments, Swapna Gottipati, Jing Jiang Dec 2012

Extracting And Normalizing Entity-Actions From Users' Comments, Swapna Gottipati, Jing Jiang

Research Collection School Of Computing and Information Systems

With the growing popularity of opinion-rich resources on the Web, new opportunities and challenges arise and aid people in actively using such information to understand the opinions of others. Opinion mining process currently focuses on extracting the sentiments of the users on products, social, political and economical issues. In many instances, users not only express their sentiments but also contribute their ideas, requests and suggestions through comments. Such comments are useful for domain experts and are referred to as actionable content. Extracting actionable knowledge from online social media has attracted a growing interest from both academia and the industry. We …


Detecting Anomalies In Bipartite Graphs With Mutual Dependency Principles, Hanbo Dai, Feida Zhu, Ee Peng Lim, Hwee Hwa Pang Dec 2012

Detecting Anomalies In Bipartite Graphs With Mutual Dependency Principles, Hanbo Dai, Feida Zhu, Ee Peng Lim, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Bipartite graphs can model many real life applications including users-rating-products in online marketplaces, users-clicking-webpages on the World Wide Web and users referring users in social networks. In these graphs, the anomalousness of nodes in one partite often depends on that of their connected nodes in the other partite. Previous studies have shown that this dependency can be positive (the anomalousness of a node in one partite increases or decreases along with that of its connected nodes in the other partite) or negative (the anomalousness of a node in one partite rises or falls in opposite direction to that of its …


Finding Thoughtful Comments From Social Media, Gottipati Swapna, Jing Jiang Dec 2012

Finding Thoughtful Comments From Social Media, Gottipati Swapna, Jing Jiang

Research Collection School Of Computing and Information Systems

Online user comments contain valuable user opinions. Comments vary greatly in quality and detecting high quality comments is a subtask of opinion mining and summarization research. Finding attentive comments that provide some reasoning is highly valuable in understanding the user’s opinion particularly in sociopolitical opinion mining and aids policy makers, social organizations or government sectors in decision making. In this paper we study the problem of detecting thoughtful comments. We empirically study various textual features, discourse relations and relevance features to predict thoughtful comments. We use logistic regression model and test on the datasets related to sociopolitical content. We found …


Do Hackers Seek Variety? An Empirical Analysis Of Website Defacements, Kok Wei Ooi, Seung-Hyun Kim, Qiu-Hong Wang, Kai Lung Hui Dec 2012

Do Hackers Seek Variety? An Empirical Analysis Of Website Defacements, Kok Wei Ooi, Seung-Hyun Kim, Qiu-Hong Wang, Kai Lung Hui

Research Collection School Of Computing and Information Systems

The importance of securing the cyberspace is higher than ever along with the evolution of cyber attacks launched by hackers with malicious intention. However, there has been little research to understand the hackers who are the most important agents determining the landscape of information security. This paper investigates the behaviors of hackers using a longitudinal dataset of defacement attacks. Based on theories of economics of criminal behaviors and variety seeking, we find that hackers seek variety in choosing their victims in terms of region, hacking method, and the type of operating systems; as their prior experience is focused in terms …


Investigating Intelligent Agents In A 3d Virtual World, Yilin Kang, Fiona Fui-Hoon Nah, Ah-Hwee Tan Dec 2012

Investigating Intelligent Agents In A 3d Virtual World, Yilin Kang, Fiona Fui-Hoon Nah, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Web 3.0 involves "intelligent" web applications that utilize natural language processing, machine-based learning and reasoning, and intelligent techniques to analyze and understand user behavior. In this research, we empirically assess a specific form of Web 3.0 application in the form of intelligent agents that offer assistance to users in the virtual world. Using media naturalness theory, we hypothesize that the use of intelligent agents in the virtual world can enhance user experience by offering a more natural way of communication and assistance to users. We are interested to test if media naturalness theory holds in the context of intelligent agents …


Knowledge-Based Exploration For Reinforcement Learning In Self-Organizing Neural Networks, Teck-Hou Teng, Ah-Hwee Tan Dec 2012

Knowledge-Based Exploration For Reinforcement Learning In Self-Organizing Neural Networks, Teck-Hou Teng, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Exploration is necessary during reinforcement learning to discover new solutions in a given problem space. Most reinforcement learning systems, however, adopt a simple strategy, by randomly selecting an action among all the available actions. This paper proposes a novel exploration strategy, known as Knowledge-based Exploration, for guiding the exploration of a family of self-organizing neural networks in reinforcement learning. Specifically, exploration is directed towards unexplored and favorable action choices while steering away from those negative action choices that are likely to fail. This is achieved by using the learned knowledge of the agent to identify prior action choices leading to …


Agent-Based Virtual Humans In Co-Space: An Evaluative Study, Yilin Kang, Ah-Hwee Tan, Fiona Fui-Hoon Nah Dec 2012

Agent-Based Virtual Humans In Co-Space: An Evaluative Study, Yilin Kang, Ah-Hwee Tan, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

Co-Space refers to interactive virtual environment modelled after the real world in terms of look-and-feel, functionalities and services. We have developed a 3D virtual world named Nan yang Technological University (NTU) Co-Space populated with virtual human characters. Three key requirements of realistic virtual humans in the virtual world have been identified, namely (1) autonomy: agents can function on their own, (2) interactivity: agents can interact naturally with players, and (3) personality: agents can exhibit human traits and characteristics. Working towards these challenges, we propose a brain-inspired agent architecture that integrates goal-directed autonomy, natural language interaction and human-like personality. We conducted …


Audit Mechanisms For Provable Risk Management And Accountable Data Governance, Jeremiah Blocki, Nicolas Christin, Anupam Datta, Arunesh Sinha Nov 2012

Audit Mechanisms For Provable Risk Management And Accountable Data Governance, Jeremiah Blocki, Nicolas Christin, Anupam Datta, Arunesh Sinha

Research Collection School Of Computing and Information Systems

Organizations that collect and use large volumes of personal information are expected under the principle of accountable data governance to take measures to protect data subjects from risks that arise from inapproriate uses of this information. In this paper, we focus on a specific class of mechanisms—audits to identify policy violators coupled with punishments—that organizations such as hospitals, financial institutions, and Web services companies may adopt to protect data subjects from privacy and security risks stemming from inappropriate information use by insiders. We model the interaction between the organization (defender) and an insider (adversary) during the audit process as a …


Joint Topic Modeling For Event Summarization Across News And Social Media Streams, Wei Gao, Peng Li, Kareem Darwish Nov 2012

Joint Topic Modeling For Event Summarization Across News And Social Media Streams, Wei Gao, Peng Li, Kareem Darwish

Research Collection School Of Computing and Information Systems

Social media streams such as Twitter are regarded as faster first-hand sources of information generated by massive users. The content diffused through this channel, although noisy, provides important complement and sometimes even a substitute to the traditional news media reporting. In this paper, we propose a novel unsupervised approach based on topic modeling to summarize trending subjects by jointly discovering the representative and complementary information from news and tweets. Our method captures the content that enriches the subject matter by reinforcing the identification of complementary sentence-tweet pairs. To valuate the complementarity of a pair, we leverage topic modeling formalism by …


Vireo@Trecvid 2012: Searching With Topology, Recounting Will Small Concepts, Learning With Free Examples, Wei Zhang, Chun-Chet Tan, Shi-Ai Zhu, Ting Yao, Lei Pang, Chong-Wah Ngo Nov 2012

Vireo@Trecvid 2012: Searching With Topology, Recounting Will Small Concepts, Learning With Free Examples, Wei Zhang, Chun-Chet Tan, Shi-Ai Zhu, Ting Yao, Lei Pang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

The vireo group participated in four tasks: instance search, multimedia event recounting, multimedia event detection, and semantic indexing. In this paper, we will present our approaches and discuss the evaluation results.


Impact Of Multimedia In Sina Weibo: Popularity And Life Span, Xun Zhao, Feida Zhu, Weining Qian, Aoying Zhou Nov 2012

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 SinaWeibo. Multimedia contents …


A Generalized Cluster Centroid Based Classifier For Text Categorization, Guansong Pang, Shengyi Jiang Nov 2012

A Generalized Cluster Centroid Based Classifier For Text Categorization, Guansong Pang, Shengyi Jiang

Research Collection School Of Computing and Information Systems

In this paper, a Generalized Cluster Centroid based Classifier (GCCC) and its variants for text categorization are proposed by utilizing a clustering algorithm to integrate two wellknown classifiers, i.e., the K-nearest-neighbor (KNN) classifier and the Rocchio classifier. KNN, a lazy learning method, suffers from inefficiency in online categorization while achieving remarkable effectiveness. Rocchio, which has efficient categorization performance, fails to obtain an expressive categorization model due to its inherent linear separability assumption. Our proposed method mainly focuses on two points: one point is that we use a clustering algorithm to strengthen the expressiveness of the Rocchio model; another one is …


Mining Coherent Anomaly Collections On Web Data, Hanbo Dai, Feida Zhu, Ee-Peng Lim, Hwee Hwa Pang Nov 2012

Mining Coherent Anomaly Collections On Web Data, Hanbo Dai, Feida Zhu, Ee-Peng Lim, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

The recent boom of weblogs and social media has attached increasing importance to the identification of suspicious users with unusual behavior, such as spammers or fraudulent reviewers. A typical spamming strategy is to employ multiple dummy accounts to collectively promote a target, be it a URL or a product. Consequently, these suspicious accounts exhibit certain coherent anomalous behavior identifiable as a collection. In this paper, we propose the concept of Coherent Anomaly Collection (CAC) to capture this kind of collections, and put forward an efficient algorithm to simultaneously find the top-K disjoint CACs together with their anomalous behavior patterns. Compared …


Cognitive Architectures And Autonomy: Commentary And Response, Włodzisław Duch, Ah-Hwee Tan, Stan Franklin Nov 2012

Cognitive Architectures And Autonomy: Commentary And Response, Włodzisław Duch, Ah-Hwee Tan, Stan Franklin

Research Collection School Of Computing and Information Systems

This paper provides a very useful and promising analysis and comparison of current architectures of autonomous intelligent systems acting in real time and specific contexts, with all their constraints. The chosen issue of Cognitive Architectures and Autonomy is really a challenge for AI current projects and future research. I appreciate and endorse not only that challenge but many specific choices and claims; in particular: (i) that “autonomy” is a key concept for general intelligent systems; (ii) that “a core issue in cognitive architecture is the integration of cognitive processes ....”; (iii) the analysis of features and capabilities missing in current …


Fast And Accurate Psd Matrix Estimation By Row Reduction, Hiroshi Kuwajima, Takashi Washio, Ee Peng Lim Nov 2012

Fast And Accurate Psd Matrix Estimation By Row Reduction, Hiroshi Kuwajima, Takashi Washio, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Fast and accurate estimation of missing relations, e.g., similarity, distance and kernel, among objects is now one of the most important techniques required by major data mining tasks, because the missing information of the relations is needed in many applications such as economics, psychology, and social network communities. Though some approaches have been proposed in the last several years, the practical balance between their required computation amount and obtained accuracy are insufficient for some class of the relation estimation. The objective of this paper is to formalize a problem to quickly and efficiently estimate missing relations among objects from the …


Divad: A Dynamic And Interactive Visual Analytical Dashboard For Exploring And Analyzing Transport Data, Tin Seong Kam, Ketan Barshikar, Shaun Jun Hua Tan Nov 2012

Divad: A Dynamic And Interactive Visual Analytical Dashboard For Exploring And Analyzing Transport Data, Tin Seong Kam, Ketan Barshikar, Shaun Jun Hua Tan

Research Collection School Of Computing and Information Systems

The advances in location-based data collection technologies such as GPS, RFID etc. and the rapid reduction of their costs provide us with a huge and continuously increasing amount of data about movement of vehicles, people and goods in an urban area. This explosive growth of geospatially-referenced data has far outpaced the planner’s ability to utilize and transform the data into insightful information thus creating an adverse impact on the return on the investment made to collect and manage this data. Addressing this pressing need, we designed and developed DIVAD, a dynamic and interactive visual analytics dashboard to allow city planners …


A Unified Learning Framework For Auto Face Annotation By Mining Web Facial Images, Dayong Wang, Steven C. H. Hoi, Ying He Nov 2012

A Unified Learning Framework For Auto Face Annotation By Mining Web Facial Images, Dayong Wang, Steven C. H. Hoi, Ying He

Research Collection School Of Computing and Information Systems

Auto face annotation plays an important role in many real-world multimedia information and knowledge management systems. Recently there is a surge of research interests in mining weakly-labeled facial images on the internet to tackle this long-standing research challenge in computer vision and image understanding. In this paper, we present a novel unified learning framework for face annotation by mining weakly labeled web facial images through interdisciplinary efforts of combining sparse feature representation, content-based image retrieval, transductive learning and inductive learning techniques. In particular, we first introduce a new search-based face annotation paradigm using transductive learning, and then propose an effective …


Cross-View Graph Embedding, Zhiwu Huang, S. Shan, H. Zhang, S. Lao, X. Chen Nov 2012

Cross-View Graph Embedding, Zhiwu Huang, S. Shan, H. Zhang, S. Lao, X. Chen

Research Collection School Of Computing and Information Systems

Recently, more and more approaches are emerging to solve the cross-view matching problem where reference samples and query samples are from different views. In this paper, inspired by Graph Embedding, we propose a unified framework for these cross-view methods called Cross-view Graph Embedding. The proposed framework can not only reformulate most traditional cross-view methods (e.g., CCA, PLS and CDFE), but also extend the typical single-view algorithms (e.g., PCA, LDA and LPP) to cross-view editions. Furthermore, our general framework also facilitates the development of new cross-view methods. In this paper, we present a new algorithm named Cross-view Local Discriminant Analysis (CLODA) …


Video Hyperlinking: Libraries And Tools For Threading And Visualizing Large Video Collection, Lei Pang, Wei Zhang, Hung-Khoon Tan, Chong-Wah Ngo Nov 2012

Video Hyperlinking: Libraries And Tools For Threading And Visualizing Large Video Collection, Lei Pang, Wei Zhang, Hung-Khoon Tan, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

While HTML documents could be effortlessly hyperlinked by markup tags, creation of the hyperlinks for multimedia objects is by no means easy due to the involvement of various visual processing units and intensive computational overhead. This paper introduces an open source, named VIREO-VH, which provides end-to-end support for creating hyperlinks to thread and visualize collections of videos. The software components include video pre-processing, bag-ofwords based inverted file indexing for scalable near-duplicate keyframe search, localization of partial near-duplicate segments, and galaxy visualization of video collection. The open source has been internally used by VIREO research team since 2007, and was evolved …


Multiview Semi-Supervised Learning With Consensus, Guangxia Li, Kuiyu Chang, Steven C. H. Hoi Nov 2012

Multiview Semi-Supervised Learning With Consensus, Guangxia Li, Kuiyu Chang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications. Semi-supervised learning aims to improve the performance of a classifier trained with limited number of labeled data by utilizing the unlabeled ones. This paper demonstrates a way to improve the transductive SVM, which is an existing semi-supervised learning algorithm, by employing a multiview learning paradigm. Multiview learning is based on the fact that for some problems, there may exist multiple perspectives, so called views, of each data sample. For example, in text classification, the typical view contains a large number of raw content features such …


Entity Synonyms For Structured Web Search, Tao Cheng, Hady W. Lauw, Stelios Paparizos Oct 2012

Entity Synonyms For Structured Web Search, Tao Cheng, Hady W. Lauw, Stelios Paparizos

Research Collection School Of Computing and Information Systems

Nowadays, there are many queries issued to search engines targeting at finding values from structured data (e.g., movie showtime of a specific location). In such scenarios, there is often a mismatch between the values of structured data (how content creators describe entities) and the web queries (how different users try to retrieve them). Therefore, recognizing the alternative ways people use to reference an entity, is crucial for structured web search. In this paper, we study the problem of automatic generation of entity synonyms over structured data toward closing the gap between users and structured data. We propose an offline, data-driven …


Talk Versus Work: Characteristics Of Developer Collaboration On The Jazz Platform, Subhajit Datta, Renuka Sindhgatta, Bikram Sengupta Oct 2012

Talk Versus Work: Characteristics Of Developer Collaboration On The Jazz Platform, Subhajit Datta, Renuka Sindhgatta, Bikram Sengupta

Research Collection School Of Computing and Information Systems

IBM's Jazz initiative offers a state-of-the-art collaborative development environment (CDE) facilitating developer interactions around interdependent units of work. In this paper, we analyze development data across two versions of a major IBM product developed on the Jazz platform, covering in total 19 months of development activity, including 17,000+ work items and 61,000+ comments made by more than 190 developers in 35 locations. By examining the relation between developer talk and work, we find evidence that developers maintain a reasonably high level of connectivity with peer developers with whom they share work dependencies, but the span of a developer's communication goes …


The Shanghai-Hongkong Team At Mediaeval2012: Violent Scene Detection Using Trajectory-Based Features, Yu-Gang Jiang, Qi Dai, Chun Chet Tan, Xiangyang Xue, Chong-Wah Ngo Oct 2012

The Shanghai-Hongkong Team At Mediaeval2012: Violent Scene Detection Using Trajectory-Based Features, Yu-Gang Jiang, Qi Dai, Chun Chet Tan, Xiangyang Xue, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

The Violent Scene Detection task offers a very practical challenge in detecting complex and diverse violent video clips in movies. In this working note paper, we will briefly describe our system and discuss the results, which achieved top performance in mAP@201 and runner-up in mAP@100, among all 35 submissions worldwide. The central component of our system is a set of features derived from the appearance and motion of local patch trajectories [2]. We use these features and SVM classifier as the baseline approach and add in a few other components to further improve the performance. Our findings indicate that the …


Influentials, Novelty, And Social Contagion: The Viral Power Of Average Friends, Close Communities, And Old News, Nicholas Harrigan, Palakorn Achananuparp, Ee Peng Lim Oct 2012

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 …