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- Social media (5)
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- Recommendation system (2)
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- Ageing-in-place (1)
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Articles 1 - 30 of 37
Full-Text Articles in Physical Sciences and Mathematics
Capstone Projects Mining System For Insights And Recommendations, Melvrivk Aik Chun Goh, Swapna Gottipati, Venky Shankararaman
Capstone Projects Mining System For Insights And Recommendations, Melvrivk Aik Chun Goh, Swapna Gottipati, Venky Shankararaman
Research Collection School Of Computing and Information Systems
In this paper, we present a classification based system to discover knowledge and trends in higher education students’ projects. Essentially, the educational capstone projects provide an opportunity for students to apply what they have learned and prepare themselves for industry needs. Therefore mining such projects gives insights of students’ experiences as well as industry project requirements and trends. In particular, we mine capstone projects executed by Information Systems students to discover patterns and insights related to people, organization, domain, industry needs and time. We build a capstone projects mining system (CPMS) based on classification models that leverage text mining, natural …
Modeling Social Media Content With Word Vectors For Recommendation, Ying Ding, Jing Jiang
Modeling Social Media Content With Word Vectors For Recommendation, Ying Ding, Jing Jiang
Research Collection School Of Computing and Information Systems
In social media, recommender systems are becoming more and more important. Different techniques have been designed for recommendations under various scenarios, but many of them do not use user-generated content, which potentially reflects users’ opinions and interests. Although a few studies have tried to combine user-generated content with rating or adoption data, they mostly reply on lexical similarity to calculate textual similarity. However, in social media, a diverse range of words is used. This renders the traditional ways of calculating textual similarity ineffective. In this work, we apply vector representation of words to measure the semantic similarity between text. We …
Whom Should We Sense In 'Social Sensing' - Analyzing Which Users Work Best For Social Media Now-Casting, Jisun An, Ingmar Weber
Whom Should We Sense In 'Social Sensing' - Analyzing Which Users Work Best For Social Media Now-Casting, Jisun An, Ingmar Weber
Research Collection School Of Computing and Information Systems
Given the ever increasing amount of publicly available social media data, there is growing interest in using online data to study and quantify phenomena in the offline 'real' world. As social media data can be obtained in near real-time and at low cost, it is often used for 'now-casting' indices such as levels of flu activity or unemployment. The term 'social sensing' is often used in this context to describe the idea that users act as 'sensors', publicly reporting their health status or job losses. Sensor activity during a time period is then typically aggregated in a 'one tweet, one …
Where Are The Passengers? A Grid-Based Gaussian Mixture Model For Taxi Bookings, Meng-Fen Chiang, Tuan Anh Hoang, Ee-Peng Lim
Where Are The Passengers? A Grid-Based Gaussian Mixture Model For Taxi Bookings, Meng-Fen Chiang, Tuan Anh Hoang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Taxi bookings are events where requests for taxis are made by passengers either over voice calls or mobile apps. As the demand for taxis changes with space and time, it is important to model both the space and temporal dimensions in dynamic booking data. Several applications can benefit from a good taxi booking model. These include the prediction of number of bookings at certain location and time of the day, and the detection of anomalous booking events. In this paper, we propose a Grid-based Gaussian Mixture Model (GGMM) with spatio-temporal dimensions that groups booking data into a number of spatio-temporal …
Intelligshop: Enabling Intelligent Shopping In Malls Through Location-Based Augmented Reality, Aditi Adhikari, Vincent W. Zheng, Hong Cao, Miao Lin, Yuan Fang, Kevin Chen-Chuan Chang
Intelligshop: Enabling Intelligent Shopping In Malls Through Location-Based Augmented Reality, Aditi Adhikari, Vincent W. Zheng, Hong Cao, Miao Lin, Yuan Fang, Kevin Chen-Chuan Chang
Research Collection School Of Computing and Information Systems
Shopping experience is important for both citizens and tourists. We present IntelligShop, a novel location-based augmented reality application that supports intelligent shopping experience in malls. As the key functionality, IntelligShop provides an augmented reality interface-people can simply use ubiquitous smartphones to face mall retailers, then IntelligShop will automatically recognize the retailers and fetch their online reviews from various sources (including blogs, forums and publicly accessible social media) to display on the phones. Technically, IntelligShop addresses two challenging data mining problems, including robust feature learning to support heterogeneous smartphones in localization and learning to query for automatically gathering the retailer content …
Targeted Blended Learning Through Competency Assessment In An Undergraduate Information Systems Program, Joelle Elmaleh, Shankararaman, Venky
Targeted Blended Learning Through Competency Assessment In An Undergraduate Information Systems Program, Joelle Elmaleh, Shankararaman, Venky
Research Collection School Of Computing and Information Systems
In this paper we report our study on the problem of competency acquisition when students progress from one course to another and more generally, from one term to the next. We observed that some students moved on to a second programming course without acquiring some of the competencies in the first programming course. This leads to problem in the second course, especially when these competencies are pre-requisites for this course. We applied blended learning, which allows a student to learn at least in part through delivery of content and instruction via online media, to overcome this problem. Our approach is …
Shineseniors: Personalized Services For Active Ageing-In-Place, Liming Bai, Alex I. Gavino, Wei Qi Lee, Jungyoon Kim, Na Liu, Hwee-Pink Tan, Hwee Xian Tan, Lee Buay Tan, Xiaoping Toh, Alvin Cerdena Valera, Elina Jia Yu, Alfred Wu, Mark S. Fox
Shineseniors: Personalized Services For Active Ageing-In-Place, Liming Bai, Alex I. Gavino, Wei Qi Lee, Jungyoon Kim, Na Liu, Hwee-Pink Tan, Hwee Xian Tan, Lee Buay Tan, Xiaoping Toh, Alvin Cerdena Valera, Elina Jia Yu, Alfred Wu, Mark S. Fox
Research Collection School Of Computing and Information Systems
Singapore faces a major challenge in providing care and support for senior citizens due to its rapidlyageing population and declining old-age support ratio. The concept of Ageing-in-Place was introduced by the Singapore government [1] to allow older people to live independently in their own homes and communities so that the need for institutionalised care will only be utilised when necessary. We have three fundamental questions that this project will answer: 1. How to make community care serviceseffective through innovations in care delivery? How to lower the cost of service delivery and improve 2. productivity of caregivers, by leveraging information and …
Two Formulas For Success In Social Media: Learning And Network Effects, Liangfei Qiu, Qian Tang, Andrew B. Whinston
Two Formulas For Success In Social Media: Learning And Network Effects, Liangfei Qiu, Qian Tang, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
Recent years have witnessed an unprecedented explosion in information technology that enables dynamic diffusion of user-generated content in social networks. Online videos, in particular, have changed the landscape of marketing and entertainment, competing with premium content and spurring business innovations. In the present study, we examine how learning and network effects drive the diffusion of online videos. While learning happens through informational externalities, network effects are direct payoff externalities. Using a unique data set from YouTube, we empirically identify learning and network effects separately, and find that both mechanisms have statistically and economically significant effects on video views; furthermore, the …
What's Hot In Software Engineering Twitter Space?, Abhishek Sharma, Tian Yuan, David Lo
What's Hot In Software Engineering Twitter Space?, Abhishek Sharma, Tian Yuan, David Lo
Research Collection School Of Computing and Information Systems
Twitter is a popular means to disseminate information and currently more than 300 million people are using it actively. Software engineers are no exception; Singer et al. have shown that many developers use Twitter to stay current with recent technological trends. At various time points, many users are posting microblogs (i.e., tweets) about the same topic in Twitter. We refer to this reasonably large set of topically-coherent microblogs in the Twitter space made at a particular point in time as an event. In this work, we perform an exploratory study on software engineering related events in Twitter. We collect a …
Mood Self-Assessment On Smartphones, Le Minh Khue, Eng Lieh Ouh, Stan Jarzabek
Mood Self-Assessment On Smartphones, Le Minh Khue, Eng Lieh Ouh, Stan Jarzabek
Research Collection School Of Computing and Information Systems
Mood has been systematically studied by psychologists for over 100 years. As mood is a subjective feeling, any study of mood must take into account and accurately capture user’s perception of an experienced feeling. In last 40 years, a number of pen-andpaper mood self-assessment scales have been proposed. Typically, a person is asked to separately rate various dimensions of the experienced feeling (e.g., pleasure and arousal) or mood items (interested, agitated, excited, etc.) on numeric scales (e.g., between 0 and 10). These partial ratings are then combined into an overall mood rating (or into its positive and negative affect). Penand-paper …
Social Signal Processing For Real-Time Situational Understanding: A Vision And Approach, Kasthuri Jeyarajah, Shuchao Yao, Raghava Muthuraju, Archan Misra, Geeth De Mel, Julie Skipper, Tarek Abdelzaher, Michael Kolodny
Social Signal Processing For Real-Time Situational Understanding: A Vision And Approach, Kasthuri Jeyarajah, Shuchao Yao, Raghava Muthuraju, Archan Misra, Geeth De Mel, Julie Skipper, Tarek Abdelzaher, Michael Kolodny
Research Collection School Of Computing and Information Systems
The US Army Research Laboratory (ARL) and the Air Force Research Laboratory (AFRL) have established a collaborative research enterprise referred to as the Situational Understanding Research Institute (SURI). The goal is to develop an information processing framework to help the military obtain real-time situational awareness of physical events by harnessing the combined power of multiple sensing sources to obtain insights about events and their evolution. It is envisioned that one could use such information to predict behaviors of groups, be they local transient groups (e.g., protests) or widespread, networked groups, and thus enable proactive prevention of nefarious activities. This paper …
Did You Expect Your Users To Say This?: Distilling Unexpected Micro-Reviews For Venue Owners, Wen-Haw Chong, Bingtian Dai, Ee-Peng Lim
Did You Expect Your Users To Say This?: Distilling Unexpected Micro-Reviews For Venue Owners, Wen-Haw Chong, Bingtian Dai, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
With social media platforms such as Foursquare, users can now generate concise reviews, i.e. micro-reviews, about entities such as venues (or products). From the venue owner's perspective, analysing these micro-reviews will offer interesting insights, useful for event detection and customer relationship management. However not all micro-reviews are equally important, especially since a venue owner should already be familiar with his venue's primary aspects. Instead we envisage that a venue owner will be interested in micro-reviews that are unexpected to him. These can arise in many ways, such as users focusing on easily overlooked aspects (by the venue owner), making comparisons …
Designing Bus Transit Services For Routine Crowd Situations At Large Event Venues, Jianli Du, Shih-Fen Cheng, Hoong Chuin Lau
Designing Bus Transit Services For Routine Crowd Situations At Large Event Venues, Jianli Du, Shih-Fen Cheng, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
We are concerned with the routine crowd management problem after a major event at a known venue. Without properly design complementary transport services, such sudden crowd build-ups will overwhelm the existing infrastructure. In this paper, we introduce a novel flow-rate based model to model the dynamic movement of passengers over the transportation flow network. Based on this basic model, an integer linear programming model is proposed to solve the bus transit problem permanently. We validate our model against a real scenario in Singapore, where a newly constructed mega-stadium hosts various large events regularly. The results show that the proposed approach …
On Mining Lifestyles From User Trip Data, Meng-Fen Chiang, Ee-Peng Lim
On Mining Lifestyles From User Trip Data, Meng-Fen Chiang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Large cities today are facing major challenges in planning and policy formulation to keep their growth sustainable. In this paper, we aim to gain useful insights about people living in a city by developing novel models to mine user lifestyles represented by the users' activity centers. Two models, namely ACMM and ACHMM, have been developed to learn the activity centers of each user using a large dataset of bus and subway train trips performed by passengers in Singapore. We show that ACHMM and ACMM yield similar accuracies in location prediction task. We also propose methods to automatically predict "home", "work" …
Cooperation In Delay-Tolerant Networks With Wireless Energy Transfer: Performance Analysis And Optimization, Dusit Niyato, Ping Wang, Hwee-Pink Tan, Walid Saad, Dong In Kim
Cooperation In Delay-Tolerant Networks With Wireless Energy Transfer: Performance Analysis And Optimization, Dusit Niyato, Ping Wang, Hwee-Pink Tan, Walid Saad, Dong In Kim
Research Collection School Of Computing and Information Systems
We consider a delay-tolerant network (DTN) whose mobile nodes are assigned to collect packets from data sources and deliver them to a sink (i.e., a gateway). Each mobile node operates by using energy transferred wirelessly from the gateway. For such a network, two main issues are studied. First, when a mobile node is at the data source, this node must decide on whether to accept the packet received from the data source or not. In contrast, whenever a mobile node is at the gateway, it has to decide on whether to transmit the packets collected from the data sources or …
Structured Learning From Heterogeneous Behavior For Social Identity Linkage, Siyuan Liu, Shuhui Wang, Feida Zhu
Structured Learning From Heterogeneous Behavior For Social Identity Linkage, Siyuan Liu, Shuhui Wang, Feida Zhu
Research Collection School Of Computing and Information Systems
Social identity linkage across different social media platforms is of critical importance to business intelligence by gaining from social data a deeper understanding and more accurate profiling of users. In this paper, we propose a solution framework, HYDRA, which consists of three key steps: (I) we model heterogeneous behavior by long-term topical distribution analysis and multi-resolution temporal behavior matching against high noise and information missing, and the behavior similarity are described by multi-dimensional similarity vector for each user pair; (II) we build structure consistency models to maximize the structure and behavior consistency on users' core social structure across different platforms, …
Cross-Promotion In Social Media: Choosing The Right Allies, Tingting Song, Qian Tang
Cross-Promotion In Social Media: Choosing The Right Allies, Tingting Song, Qian Tang
Research Collection School Of Computing and Information Systems
This paper investigates the strategic use of cross-promotion for content producers in social media. In particular, we study how a producer chooses other producers to cross-promote so as to maximize the expected benefits of them cross-promoting him/her in return. Theories on homophily effect and social influence suggest that cross-promoted producers are more likely to cross-promote the initiator in return when they are in the similar categories or share more common friends and when the initiator has higher status. However, the cross-promotion from producers of different categories and social groups (i.e., share fewer common friends) tend to benefit the initiator more. …
Fast Optimal Aggregate Point Search For A Merged Set On Road Networks, Weiwei Sun, Chong Chen, Baihua Zheng, Chunan Chen, Liang Zhu, Weimo Liu, Yan Huang
Fast Optimal Aggregate Point Search For A Merged Set On Road Networks, Weiwei Sun, Chong Chen, Baihua Zheng, Chunan Chen, Liang Zhu, Weimo Liu, Yan Huang
Research Collection School Of Computing and Information Systems
Aggregate nearest neighbor query, which returns an optimal target 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 two algorithms to process MANN query on road networks when aggregate function is max. Then, we extend the algorithms …
Should We Use The Sample? Analyzing Datasets Sampled From Twitter's Stream Api, Yazhe Wang, Jamie Callan, Baihua Zheng
Should We Use The Sample? Analyzing Datasets Sampled From Twitter's Stream Api, Yazhe Wang, Jamie Callan, Baihua Zheng
Research Collection School Of Computing and Information Systems
Researchers have begun studying content obtained from microblogging services such as Twitter to address a variety of technological, social, and commercial research questions. The large number of Twitter users and even larger volume of tweets often make it impractical to collect and maintain a complete record of activity; therefore, most research and some commercial software applications rely on samples, often relatively small samples, of Twitter data. For the most part, sample sizes have been based on availability and practical considerations. Relatively little attention has been paid to how well these samples represent the underlying stream of Twitter data. To fill …
Retail Precinct Management: A Case Of Commercial Decentralization In Singapore, Robert De Souza, Hoong Chuin Lau, Mark Goh, Lindawati, Wee-Siong Ng, Puay-Siew Tan
Retail Precinct Management: A Case Of Commercial Decentralization In Singapore, Robert De Souza, Hoong Chuin Lau, Mark Goh, Lindawati, Wee-Siong Ng, Puay-Siew Tan
Research Collection School Of Computing and Information Systems
The synchronized last mile logistics concept seeks to address, through coordinated collaboration, several challenges that hinder reliability, cost efficiency, effective resource planning, scheduling and utilization; and increasingly, sustainability objectives. Subsequently, the meeting of service level and contractual commitments are competitively impacted with any loss of efficiency. These challenges, against a backdrop of Singapore, can essentially be addressed in selected industry sectors through a better understanding of logistics structures; innovative supply chain designs and coordination of services, operations and processes coupled with concerted policies and supply chain strategies.
Author Topic Model-Based Collaborative Filtering For Personalized Poi Recommendations, Shuhui Jiang, Xueming Qian, Jialie Shen, Yun Fu, Tao Mei
Author Topic Model-Based Collaborative Filtering For Personalized Poi Recommendations, Shuhui Jiang, Xueming Qian, Jialie Shen, Yun Fu, Tao Mei
Research Collection School Of Computing and Information Systems
From social media has emerged continuous needs for automatic travel recommendations. Collaborative filtering (CF) is the most well-known approach. However, existing approaches generally suffer from various weaknesses. For example, sparsity can significantly degrade the performance of traditional CF. If a user only visits very few locations, accurate similar user identification becomes very challenging due to lack of sufficient information for effective inference. Moreover, existing recommendation approaches often ignore rich user information like textual descriptions of photos which can reflect users' travel preferences. The topic model (TM) method is an effective way to solve the "sparsity problem," but is still far …
Efficient Reverse Top-K Boolean Spatial Keyword Queries On Road Networks, Yunjun Gao, Xu Qin, Baihua Zheng, Gang Chen
Efficient Reverse Top-K Boolean Spatial Keyword Queries On Road Networks, Yunjun Gao, Xu Qin, Baihua Zheng, Gang Chen
Research Collection School Of Computing and Information Systems
Reverse k nearest neighbor (RkNN) queries have a broad application base such as decision support, profile-based marketing, and resource allocation. Previous work on RkNN search does not take textual information into consideration or limits to the Euclidean space. In the real world, however, most spatial objects are associated with textual information and lie on road networks. In this paper, we introduce a new type of queries, namely, reverse top-k Boolean spatial keyword (RkBSK) retrieval, which assumes objects are on the road network and considers both spatial and textual information. Given a data set P on a road network and a …
Solving Multi-Vehicle Profitable Tour Problem Via Knowledge Adoption In Evolutionary Bi-Level Programming, Stephanus Daniel Handoko, Abhishek Gupta, Chen Kim Heng, Hoong Chuin Lau, Yew Soon Ong, Puay Siew Tan
Solving Multi-Vehicle Profitable Tour Problem Via Knowledge Adoption In Evolutionary Bi-Level Programming, Stephanus Daniel Handoko, Abhishek Gupta, Chen Kim Heng, Hoong Chuin Lau, Yew Soon Ong, Puay Siew Tan
Research Collection School Of Computing and Information Systems
Profitable tour problem (PTP) belongs to the class of vehicle routing problem (VRP) with profits seeking to maximize the difference between the total collected profit and the total cost incurred. Traditionally, PTP involves single vehicle. In this paper, we consider PTP with multiple vehicles. Unlike the classical VRP that seeks to serve all customers, PTP involves the strategic-level customer selection so as to maximize the total collected profit and the operational-level route optimization to minimize the total cost incurred. Therefore, PTP is essentially the knapsack problem at the strategic level with VRP at the operational level. That means the evolutionary …
Characterizing Silent Users In Social Media Communities, Gong Wei, Ee-Peng Lim, Feida Zhu
Characterizing Silent Users In Social Media Communities, Gong Wei, Ee-Peng Lim, Feida Zhu
Research Collection School Of Computing and Information Systems
Silent users often constitute a significant proportion of an online user-generated content system. In the context of social media such as Twitter, users can opt to be silent all or most of the time. They are often called the invisible participants or lurkers. As lurkers contribute little to the online content, existing analysis often overlooks their presence and voices. However, we argue that understanding lurkers is important in many applications such as recommender systems, targeted advertising, and social sensing. This research therefore seeks to characterize lurkers in social media and propose methods to profile them. We examine 18 weeks of …
Breaking The News: First Impressions Matter On Online News, Julio Reis, Fabr´Icio Benevenuto, Pedro Olmo, Raquel Prates, Haewoon Kwak, Jisun An
Breaking The News: First Impressions Matter On Online News, Julio Reis, Fabr´Icio Benevenuto, Pedro Olmo, Raquel Prates, Haewoon Kwak, Jisun An
Research Collection School Of Computing and Information Systems
A growing number of people are changing the way they consume news, replacing the traditional physical newspapers and magazines by their virtual online versions or/and weblogs. The interactivity and immediacy present in online news are changing the way news are being produced and exposed by media corporations. News websites have to create effective strategies to catch people’s attention and attract their clicks. In this paper we investigate possible strategies used by online news corporations in the design of their news headlines. We analyze the content of 69,907 headlines produced by four major global media corporations during a minimum of eight …
Review Selection Using Micro-Reviews, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas
Review Selection Using Micro-Reviews, Thanh-Son Nguyen, Hady W. Lauw, Panayiotis Tsaparas
Research Collection School Of Computing and Information Systems
Given the proliferation of review content, and the fact that reviews are highly diverse and often unnecessarily verbose, users frequently face the problem of selecting the appropriate reviews to consume. Micro-reviews are emerging as a new type of online review content in the social media. Micro-reviews are posted by users of check-in services such as Foursquare. They are concise (up to 200 characters long) and highly focused, in contrast to the comprehensive and verbose reviews. In this paper, we propose a novel mining problem, which brings together these two disparate sources of review content. Specifically, we use coverage of micro-reviews …
Multi-Roles Affiliation Model For General User Profiling, Lizi Liao, Heyan Huang, Yashen Wang
Multi-Roles Affiliation Model For General User Profiling, Lizi Liao, Heyan Huang, Yashen Wang
Research Collection School Of Computing and Information Systems
Online social networks release user attributes, which is important for many applications. Due to the sparsity of such user attributes online, many works focus on profiling user attributes automatically. However, in order to profile a specific user attribute, an unique model is built and such model usually does not fit other profiling tasks. In our work, we design a novel, flexible general user profiling model which naturally models users’ friendships with user attributes. Experiments show that our method simultaneously profile multiple attributes with better performance.
Using Support Vector Machine Ensembles For Target Audience Classification On Twitter, Siaw Ling Lo, Raymond Chiong, David Cornforth
Using Support Vector Machine Ensembles For Target Audience Classification On Twitter, Siaw Ling Lo, Raymond Chiong, David Cornforth
Research Collection School Of Computing and Information Systems
The vast amount and diversity of the content shared on social media can pose a challenge for any business wanting to use it to identify potential customers. In this paper, our aim is to investigate the use of both unsupervised and supervised learning methods for target audience classification on Twitter with minimal annotation efforts. Topic domains were automatically discovered from contents shared by followers of an account owner using Twitter Latent Dirichlet Allocation (LDA). A Support Vector Machine (SVM) ensemble was then trained using contents from different account owners of the various topic domains identified by Twitter LDA. Experimental results …
Students’ Perspectives On Flipped Classroom Implementation In Higher Education, Joelle Elmaleh, Nachamma Sockalingam
Students’ Perspectives On Flipped Classroom Implementation In Higher Education, Joelle Elmaleh, Nachamma Sockalingam
Research Collection School Of Computing and Information Systems
This paper reports students' experiences with a Flipped Classroom pedagogy model in an undergraduate programming course and suggests ways to improve the Flipped Classroom implementation.
Chalk And Cheese In Twitter: Discriminating Personal And Organization Accounts, Richard Jayadi Oentaryo, Jia-Wei Low, Ee Peng Lim
Chalk And Cheese In Twitter: Discriminating Personal And Organization Accounts, Richard Jayadi Oentaryo, Jia-Wei Low, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Social media have been popular not only for individuals to share contents, but also for organizations to engage users and spread information. Given the trait differences between personal and organization accounts, the ability to distinguish between the two account types is important for developing better search/recommendation engines, marketing strategies, and information dissemination platforms. However, such task is non-trivial and has not been well studied thus far. In this paper, we present a new generic framework for classifying personal and organization accounts, based upon which comprehensive and systematic investigation on a rich variety of content, social, and temporal features can be …