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Research Collection School Of Computing and Information Systems

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Articles 2431 - 2460 of 3436

Full-Text Articles in Databases and Information Systems

Visualizing Media Bias Through Twitter, Jisun An, Meeyoung Cha, Gummadi, Krishna, Jon Crowcroft, Daniele Queria Jun 2012

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 …

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Spatial Queries In Wireless Broadcast Environments [Keynote Speech], Kyriakos Mouratidis May 2012

Spatial Queries In Wireless Broadcast Environments [Keynote Speech], Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

Wireless data broadcasting is a promising technique for information dissemination that exploits the computational capabilities of mobile devices, in order to enhance the scalability of the system. Under this environment, the data are continuously broadcast by the server, interleaved with some indexing information for query processing. Clients may tune in the broadcast channel and process their queries locally without contacting the server. In this paper we focus on spatial queries in particular. First, we review existing methods on this topic. Next, taking shortest path computation as an example, we showcase technical challenges arising in this processing model and describe techniques …

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Spalendar: Visualizing A Group's Calendar Events Over A Geographic Space On A Public Display, Chen Xiang, Sebastian Boring, Sheelagh Carpendale, Anthony Tang, Saul Greenberg May 2012

Spalendar: Visualizing A Group's Calendar Events Over A Geographic Space On A Public Display, Chen Xiang, Sebastian Boring, Sheelagh Carpendale, Anthony Tang, Saul Greenberg

Research Collection School Of Computing and Information Systems

Portable paper calendars (i.e., day planners and organizers) have greatly influenced the design of group electronic calendars. Both use time units (hours/days/weeks/etc.) to organize visuals, with useful information (e.g., event types, locations, attendees) usually presented as - perhaps abbreviated or even hidden - text fields within those time units. The problem is that, for a group, this visual sorting of individual events into time buckets conveys only limited information about the social network of people. For example, people’s whereabouts cannot be read ‘at a glance’ but require examining the text. Our goal is to explore an alternate visualization that can …

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Pamr: Passive-Aggressive Mean Reversion Strategy For Portfolio Selection, Bin Li, Peilin Zhao, Steven C. H. Hoi, Vivekanand Gopalkrishnan May 2012

Pamr: Passive-Aggressive Mean Reversion Strategy For Portfolio Selection, Bin Li, Peilin Zhao, Steven C. H. Hoi, Vivekanand Gopalkrishnan

Research Collection School Of Computing and Information Systems

This project proposes a novel online portfolio selection strategy named ``Passive Aggressive Mean Reversion" (PAMR). Unlike traditional trend following approaches, the proposed approach relies upon the mean reversion relation of financial markets. Equipped with online passive aggressive learning technique from machine learning, the proposed portfolio selection strategy can effectively exploit the mean reversion property of markets. By analyzing PAMR's update scheme, we find that it nicely trades off between portfolio return and volatility risk and reflects the mean reversion trading principle. We also present several variants of PAMR algorithm, including a mixture algorithm which mixes PAMR and other strategies. We …

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Organizing User Search Histories, Heasoo Hwang, Hady W. Lauw, Lise Getoor, Alexandros Ntoulas May 2012

Organizing User Search Histories, Heasoo Hwang, Hady W. Lauw, Lise Getoor, Alexandros Ntoulas

Research Collection School Of Computing and Information Systems

Users are increasingly pursuing complex task-oriented goals on the web, such as making travel arrangements, managing finances, or planning purchases. To this end, they usually break down the tasks into a few codependent steps and issue multiple queries around these steps repeatedly over long periods of time. To better support users in their long-term information quests on the web, search engines keep track of their queries and clicks while searching online. In this paper, we study the problem of organizing a user's historical queries into groups in a dynamic and automated fashion. Automatically identifying query groups is helpful for a …

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Method And Apparatus For Rapid Identification Of Column Heterogeneity, Bing Tian Dai, Nikolaos Koudas, Beng Chin Ooi, Divesh Srivastava, Suresh Venkatasubranmanian May 2012

Method And Apparatus For Rapid Identification Of Column Heterogeneity, Bing Tian Dai, Nikolaos Koudas, Beng Chin Ooi, Divesh Srivastava, Suresh Venkatasubranmanian

Research Collection School Of Computing and Information Systems

A method and apparatus for rapid identification of column heterogeneity in databases are disclosed. For example, the method receives data associated with a column in a database. The method computes a cluster entropy for the data as a measure of data heterogeneity and then determines whether said data is heterogeneous in accordance with the cluster entropy.

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Spatial Queries In Wireless Broadcast Environments [Keynote Speech], Kyriakos Mouratidis May 2012

Spatial Queries In Wireless Broadcast Environments [Keynote Speech], Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

Wireless data broadcasting is a promising technique for information dissemination that exploits the computational capabilities of mobile devices, in order to enhance the scalability of the system. Under this environment, the data are continuously broadcast by the server, interleaved with some indexing information for query processing. Clients may tune in the broadcast channel and process their queries locally without contacting the server. In this paper we focus on spatial queries in particular. First, we review existing methods on this topic. Next, taking shortest path computation as an example, we showcase technical challenges arising in this processing model and describe techniques …

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Motivated Learning For The Development Of Autonomous Agents, Janusz A. Starzyk, James T. Graham, Pawel Raif, Ah-Hwee Tan Apr 2012

Motivated Learning For The Development Of Autonomous Agents, Janusz A. Starzyk, James T. Graham, Pawel Raif, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

A new machine learning approach known as motivated learning (ML) is presented in this work. Motivated learning drives a machine to develop abstract motivations and choose its own goals. ML also provides a self-organizing system that controls a machine’s behavior based on competition between dynamically-changing pain signals. This provides an interplay of externally driven and internally generated control signals. It is demonstrated that ML not only yields a more sophisticated learning mechanism and system of values than reinforcement learning (RL), but is also more efficient in learning complex relations and delivers better performance than RL in dynamically changing environments. In …

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Mining Social Dependencies In Dynamic Interaction Networks, Freddy Chong-Tat Chua, Hady W. Lauw, Ee Peng Lim Apr 2012

Mining Social Dependencies In Dynamic Interaction Networks, Freddy Chong-Tat Chua, Hady W. Lauw, Ee Peng Lim

Research Collection School Of Computing and Information Systems

User-to-user interactions have become ubiquitous in Web 2.0. Users exchange emails, post on newsgroups, tag web pages, co-author papers, etc. Through these interactions, users co-produce or co-adopt content items (e.g., words in emails, tags in social bookmarking sites). We model such dynamic interactions as a user interaction network, which relates users, interactions, and content items over time. After some interactions, a user may produce content that is more similar to those produced by other users previously. We term this effect social dependency, and we seek to mine from such networks the degree to which a user may be socially dependent …

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Structural Analysis In Multi-Relational Social Networks, Bing Tian Dai, Freddy Chong Tat Chua, Ee-Peng Lim Apr 2012

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 …

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Obfuscating The Topical Intention In Enterprise Text Search, Hwee Hwa Pang, Xiaokui Xiao, Jialie Shen Apr 2012

Obfuscating The Topical Intention In Enterprise Text Search, Hwee Hwa Pang, Xiaokui Xiao, Jialie Shen

Research Collection School Of Computing and Information Systems

The text search queries in an enterprise can reveal the users' topic of interest, and in turn confidential staff or business information. To safeguard the enterprise from consequences arising from a disclosure of the query traces, it is desirable to obfuscate the true user intention from the search engine, without requiring it to be re-engineered. In this paper, we advocate a unique approach to profile the topics that are relevant to the user intention. Based on this approach, we introduce an (ε 1, ε 2)-privacy model that allows a user to stipulate that topics relevant to her intention …

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Detecting Extreme Rank Anomalous Collections, Hanbo Dai, Feida Zhu, Ee-Peng Lim, Hwee Hwa Pang Apr 2012

Detecting Extreme Rank Anomalous Collections, Hanbo Dai, Feida Zhu, Ee-Peng Lim, Hwee Hwa Pang

Research Collection School Of Computing and Information Systems

Anomaly or outlier detection has a wide range of applications, including fraud and spam detection. Most existing studies focus on detecting point anomalies, i.e., individual, isolated entities. However, there is an increasing number of applications in which anomalies do not occur individually, but in small collections. Unlike the majority, entities in an anomalous collection tend to share certain extreme behavioral traits. The knowledge essential in understanding why and how the set of entities becomes outliers would only be revealed by examining at the collection level. A good example is web spammers adopting common spamming techniques. To discover this kind of …

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Quality And Leniency In Online Collaborative Rating Systems, Hady W. Lauw, Ee Peng Lim, Ke Wang Mar 2012

Quality And Leniency In Online Collaborative Rating Systems, Hady W. Lauw, Ee Peng Lim, Ke Wang

Research Collection School Of Computing and Information Systems

The emerging trend of social information processing has resulted in Web users’ increased reliance on user-generated content contributed by others for information searching and decision making. Rating scores, a form of user-generated content contributed by reviewers in online rating systems, allow users to leverage others’ opinions in the evaluation of objects. In this article, we focus on the problem of summarizing the rating scores given to an object into an overall score that reflects the object’s quality. We observe that the existing approaches for summarizing scores largely ignores the effect of reviewers exercising different standards in assigning scores. Instead of …

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Road: A New Spatial Object Search Framework For Road Networks, Ken C. K. Lee, Wang-Chien Lee, Baihua Zheng, Yuan Tian Mar 2012

Road: A New Spatial Object Search Framework For Road Networks, Ken C. K. Lee, Wang-Chien Lee, Baihua Zheng, Yuan Tian

Research Collection School Of Computing and Information Systems

In this paper, we present a new system framework called ROAD for spatial object search on road networks. ROAD is extensible to diverse object types and efficient for processing various location-dependent spatial queries (LDSQs), as it maintains objects separately from a given network and adopts an effective search space pruning technique. Based on our analysis on the two essential operations for LDSQ processing, namely, network traversal and object lookup, ROAD organizes a large road network as a hierarchy of interconnected regional subnetworks (called Rnets). Each Rnet is augmented with 1) shortcuts and 2) object abstracts to accelerate network traversals and …

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Decision-Making Models, Decision Support And Problem Solving, Mark R. Lehto, Fiona Fui-Hoon Nah, Ji Soo Yi Mar 2012

Decision-Making Models, Decision Support And Problem Solving, Mark R. Lehto, Fiona Fui-Hoon Nah, Ji Soo Yi

Research Collection School Of Computing and Information Systems

This chapter focuses on the broad topic of human decision making. Decision making is often viewed as a stage of human information processing because people must gather, organize, and combine information from various sources to make decisions. However, as decisions grow more complex, information processing actually becomes part of decision making, and methods of decision sup-port that help decision makers process information become of growing importance. Decision making also overlaps with problem solving. The point where decision making becomes problem solving is fuzzy, but many decisions require problem solving, and the opposite is true as well. Cognitive models of problem …

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The Social Network Of Software Engineering Research, Subhajit Datta, Nishant Kumar, Santonu Sarkar Feb 2012

The Social Network Of Software Engineering Research, Subhajit Datta, Nishant Kumar, Santonu Sarkar

Research Collection School Of Computing and Information Systems

The social network perspective has served as a useful framework for studying scientific research collaboration in different disciplines. Although collaboration in computer science research has received some attention, software engineering research collaboration has remained unexplored to a large extent. In this paper, we examine the collaboration networks based on co-authorship information of papers from ten software engineering publication venues over the 1976-2010 time period. We compare time variations of certain parameters of these networks with corresponding parameters of collaboration networks from other disciplines. We also explore whether software engineering collaboration networks manifest symptoms of the small-world phenomenon, conform to the …

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Mitigating The True Cost Of Advertisement-Supported "Free" Mobile Applications, Azeem J. Khan, Vigneshwaran Subbaraju, Archan Misra, Srinivasan Seshan Feb 2012

Mitigating The True Cost Of Advertisement-Supported "Free" Mobile Applications, Azeem J. Khan, Vigneshwaran Subbaraju, Archan Misra, Srinivasan Seshan

Research Collection School Of Computing and Information Systems

The dominant, "ad-supported free application" model for consumer-oriented mobile computing is seemingly imperiled by the growing global adoption of metered data pricing plans by mobile operators. In this paper, we explore the opportunities for addressing this emerging conflict by enabling more intelligent ad delivery to such mobile devices. One especially promising path is leveraging the increasing availability of heterogeneous wireless access technologies (e.g., WiFi, femtocells) that offer less restrictive and more energy-efficient transport substrates for such data traffic. To understand the possibilities that exist, we first profile the advertisement traffic characteristics for some of the most popular advertisement-supported consumer applications, …

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Extreme Learning Machine Terrain-Based Navigation For Unmanned Aerial Vehicles, Ee May Kan, Meng Hiot Lim, Yew Soon Ong, Ah-Hwee Tan, Swee Ping Yeo Feb 2012

Extreme Learning Machine Terrain-Based Navigation For Unmanned Aerial Vehicles, Ee May Kan, Meng Hiot Lim, Yew Soon Ong, Ah-Hwee Tan, Swee Ping Yeo

Research Collection School Of Computing and Information Systems

Unmanned aerial vehicles (UAVs) rely on global positioning system (GPS) information to ascertain its position for navigation during mission execution. In the absence of GPS information, the capability of a UAV to carry out its intended mission is hindered. In this paper, we learn alternative means for UAVs to derive real-time positional reference information so as to ensure the continuity of the mission. We present extreme learning machine as a mechanism for learning the stored digital elevation information so as to aid UAVs to navigate through terrain without the need for GPS. The proposed algorithm accommodates the need of the …

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Self‐Regulating Action Exploration In Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Yuan-Sin Tan Jan 2012

Self‐Regulating Action Exploration In Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Yuan-Sin Tan

Research Collection School Of Computing and Information Systems

The basic tenet of a learning process is for an agent to learn for only as much and as long as it is necessary. With reinforcement learning, the learning process is divided between exploration and exploitation. Given the complexity of the problem domain and the randomness of the learning process, the exact duration of the reinforcement learning process can never be known with certainty. Using an inaccurate number of training iterations leads either to the non-convergence or the over-training of the learning agent. This work addresses such issues by proposing a technique to self-regulate the exploration rate and training duration …

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Topic Based Query Suggestions For Video Search, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia Jan 2012

Topic Based Query Suggestions For Video Search, Kong-Wah Wan, Ah-Hwee Tan, Joo-Hwee Lim, Liang-Tien Chia

Research Collection School Of Computing and Information Systems

Query suggestion is an assistive technology mechanism commonly used in search engines to enable a user to formulate their search queries by predicting or completing the next few query words that the user is likely to type. In most implementations, the suggestions are mined from query log and use some simple measure of query similarity such as query frequency or lexicographical matching. In this paper, we propose an alternative method of presenting query suggestions by their thematic topics. Our method adopts a document-centric approach to mine topics in the corpus, and does not require the availability of a query log. …

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Evaluating The Use Of A Mobile Annotation System For Geography Education, Dion Hoe-Lian Goh, Khasfariyati Razikin, Chei Sian Lee, Ee Peng Lim, Kalyani Chatterjea, Chew-Hung Chang Jan 2012

Evaluating The Use Of A Mobile Annotation System For Geography Education, Dion Hoe-Lian Goh, Khasfariyati Razikin, Chei Sian Lee, Ee Peng Lim, Kalyani Chatterjea, Chew-Hung Chang

Research Collection School Of Computing and Information Systems

Mobile devices used in educational settings are usually employed within a collaborative learning activity in which learning takes place in the form of social interactions between team members while performing a shared task. The authors aim to introduce MobiTOP (Mobile Tagging of Objects and People), a mobile annotation system that allows users to contribute and share geospatial multimedia annotations via mobile devices. Field observations and interviews were conducted. A group of trainee teachers involved in a geography field study were instructed to identify rock formations by collaborating with each other using the MobiTOP system. The trainee teachers who were in …

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Who Is Retweeting The Tweeters? Modeling, Originating, And Promoting Behaviors In The Twitter Network, Achananuparp Palakorn, Ee Peng Lim, Jing Jiang, Tuan Anh Hoang Jan 2012

Who Is Retweeting The Tweeters? Modeling, Originating, And Promoting Behaviors In The Twitter Network, Achananuparp Palakorn, Ee Peng Lim, Jing Jiang, Tuan Anh Hoang

Research Collection School Of Computing and Information Systems

Real-time microblogging systems such as Twitter offer users an easy and lightweight means to exchange information. Instead of writing formal and lengthy messages, microbloggers prefer to frequently broadcast several short messages to be read by other users. Only when messages are interesting, are they propagated further by the readers. In this article, we examine user behavior relevant to information propagation through microblogging. We specifically use retweeting activities among Twitter users to define and model originating and promoting behavior. We propose a basic model for measuring the two behaviors, a mutual dependency model, which considers the mutual relationships between the two …

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Structural Analysis In Multi-Relational Social Networks, Bingtian Dai, Freddy Chua, Ee Peng Lim Jan 2012

Structural Analysis In Multi-Relational Social Networks, Bingtian Dai, Freddy Chua, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Modern social networks often consist of multiple relations among individuals. Understanding the structure of such multi-relational network is essential. In sociology, one way of structural analysis is to identify different positions and roles using blockmodels. In this paper, we generalize stochastic blockmodels to Generalized Stochastic Blockmodels (GSBM) for performing positional and role analysis on multi-relational networks. Our GSBM generalizes many different kinds of Multivariate Probability Distribution Function (MVPDF) to model different kinds of multirelational networks. In particular, we propose to use multivariate Poisson distribution for multi-relational social networks.

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Modeling And Compressing 3-D Facial Expressions Using Geometry Videos, Jiazhi Xia, Dao T. P. Quynh, Ying He, Xiaoming Chen, Steven C. H. Hoi Jan 2012

Modeling And Compressing 3-D Facial Expressions Using Geometry Videos, Jiazhi Xia, Dao T. P. Quynh, Ying He, Xiaoming Chen, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

In this paper, we present a novel geometry video (GV) framework to model and compress 3-D facial expressions. GV bridges the gap of 3-D motion data and 2-D video, and provides a natural way to apply the well-studied video processing techniques to motion data processing. Our framework includes a set of algorithms to construct GVs, such as hole filling, geodesic-based face segmentation, expression-invariant parameterization (EIP), and GV compression. Our EIP algorithm can guarantee the exact correspondence of the salient features (eyes, mouth, and nose) in different frames, which leads to GVs with better spatial and temporal coherence than that of …

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Systems And Methods For Transaction Account Offerings, Clinton Allen, Michael Digregorio, Glade Erikson, Deepinder Gulati, Jacob Plammoottil Jacob, Sanjiv Khosla, Seema Chokshi Jan 2012

Systems And Methods For Transaction Account Offerings, Clinton Allen, Michael Digregorio, Glade Erikson, Deepinder Gulati, Jacob Plammoottil Jacob, Sanjiv Khosla, Seema Chokshi

Research Collection School Of Computing and Information Systems

A method for receiving a user input for providing offerings is disclosed. Fields may be populated for creating a database query for matching a selection of offerings to a population of customers. Data may be received from the database, in response to interactively building the query and/or executing the query. Multiple rank ordered results may be produced for comparison, wherein the producing uses preprogrammed analytics, data from the database and user input, and wherein the results include customer lists linked to a distinct offering and a preferred delivery channel of the offering to a customer. A transaction account may be …

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Tweets And Votes: A Study Of The 2011 Singapore General Election, Marko M. Skoric, Nathaniel D. Poor, Palakorn Achananuparp, Ee Peng Lim, Jing Jiang Jan 2012

Tweets And Votes: A Study Of The 2011 Singapore General Election, Marko M. Skoric, Nathaniel D. Poor, Palakorn Achananuparp, Ee Peng Lim, Jing Jiang

Research Collection School Of Computing and Information Systems

This study focuses on the uses of Twitter during the elections, examining whether the messages posted online are reflective of the climate of public opinion. Using Twitter data obtained during the official campaign period of the 2011 Singapore General Election, we test the predictive power of tweets in forecasting the election results. In line with some previous studies, we find that during the elections the Twitter sphere represents a rich source of data for gauging public opinion and that the frequency of tweets mentioning names of political parties, political candidates and contested constituencies could be used to make predictions about …

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Information Extraction From Text, Jing Jiang Jan 2012

Information Extraction From Text, Jing Jiang

Research Collection School Of Computing and Information Systems

Information extraction is the task of finding structured information from unstructured or semi-structured text. It is an important task in text mining and has been extensively studied in various research communities including natural language processing, information retrieval and Web mining. It has a wide range of applications in domains such as biomedical literature mining and business intelligence. Two fundamental tasks of information extraction are named entity recognition and relation extraction. The former refers to finding names of entities such as people, organizations and locations. The latter refers to finding the semantic relations such as FounderOf and HeadquarteredIn between entities. In …

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Preface: Trends In Natural And Machine Intelligence, Jonathan H. Chan, Ah-Hwee Tan Jan 2012

Preface: Trends In Natural And Machine Intelligence, Jonathan H. Chan, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

Trends in natural and machine intelligence are increasingly reflecting a convergence in these two well-established fields of study. The Third International Neural Network Society Winter Conference (INNS-WC 2012) was held in Bangkok, Thailand, on October 3-5, 2012. INNS-WC2012, with an aim to bring together scientists, practitioners, and students worldwide, to discuss the past, present, and future challenges and trends in the area of natural and machine intelligence. This event has been a bi-annual conference of the International Neural Network Society (INNS) to provide a forum for international researchers to exchange latest ideas and advances on neural networks and related discipline.

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An Improved K-Nearest-Neighbor Algorithm For Text Categorization, Shengyi Jiang, Guansong Pang, Meiling Wu, Limin Kuang Jan 2012

An Improved K-Nearest-Neighbor Algorithm For Text Categorization, Shengyi Jiang, Guansong Pang, Meiling Wu, Limin Kuang

Research Collection School Of Computing and Information Systems

Text categorization is a significant tool to manage and organize the surging text data. Many text categorization algorithms have been explored in previous literatures, such as KNN, Naive Bayes and Support Vector Machine. KNN text categorization is an effective but less efficient classification method. In this paper, we propose an improved KNN algorithm for text categorization, which builds the classification model by combining constrained one pass clustering algorithm and KNN text categorization. Empirical results on three benchmark corpora show that our algorithm can reduce the text similarity computation substantially and outperform the-state-of-the-art KNN, Naive Bayes and Support Vector Machine classifiers. …

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Mining Diversity On Social Media Networks, Lu Liu, Feida Zhu, Meng Jiang, Jiawei Han, Lifeng Sun, Shiqiang Yang Jan 2012

Mining Diversity On Social Media Networks, Lu Liu, Feida Zhu, Meng Jiang, Jiawei Han, Lifeng Sun, Shiqiang Yang

Research Collection School Of Computing and Information Systems

The fast development of multimedia technology and increasing availability of network bandwidth has given rise to an abundance of network data as a result of all the ever-booming social media and social websites in recent years, e.g., Flickr, Youtube, MySpace, Facebook, etc. Social network analysis has therefore become a critical problem attracting enthusiasm from both academia and industry. However, an important measure that captures a participant’s diversity in the network has been largely neglected in previous studies. Namely, diversity characterizes how diverse a given node connects with its peers. In this paper, we give a comprehensive study of this concept. …

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