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Articles 5941 - 5970 of 8479
Full-Text Articles in Computer Sciences
Mini-Track Introduction: Information Economics, Competition, Regulation, Law And Society, Eric K. Clemons, Robert John Kauffman, Thomas A. Weber
Mini-Track Introduction: Information Economics, Competition, Regulation, Law And Society, Eric K. Clemons, Robert John Kauffman, Thomas A. Weber
Research Collection School Of Computing and Information Systems
This mini-track is informed by the most modern thinking in information economics and competitive strategy, and includes many interdisciplinary applications of IS and technology.
An Approach For Clone Detection In Documentation Reuse, Dmitry V. Lutsiv, Dmitry Koznov, Hamid A. Basit, Eng Lieh Ouh, Mikhail N. Smirnov, Konstantin Y. Romanovsky
An Approach For Clone Detection In Documentation Reuse, Dmitry V. Lutsiv, Dmitry Koznov, Hamid A. Basit, Eng Lieh Ouh, Mikhail N. Smirnov, Konstantin Y. Romanovsky
Research Collection School Of Computing and Information Systems
The paper focuses on the searching method for repetitions in DocBook/DRL or plain text documents. An algorithm has been designed based on software clone detection. The algorithm supports filtering results: clones are rejected if clone length in the group is less than 5 symbols, intersection of clone groups is eliminated, meaningfulness clones are removed, the groups containing clones consisting only of XML are eliminated. Remaining search is supported: found clones are extracted from the documentation, and clone search is repeated. One step is proved to be enough. Adaptive reuse technique of Paul Bassett – Stan Jarzabek has been implemented. A …
Wenzher: Comprehensive Vertical Search For Healthcare Domain, Liqiang Nie, Tao Li, Mohammad Akbari, Jialie Shen, Tat-Seng Chua
Wenzher: Comprehensive Vertical Search For Healthcare Domain, Liqiang Nie, Tao Li, Mohammad Akbari, Jialie Shen, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Online health seeking has transformed the way of health knowledge exchange and reusability. The existing general and vertical health search engines, however, just routinely return lists of matched documents or question answer (QA) pairs, which may overwhelm the seekers or not sufficiently meet the seekers’ expectations. Instead, our multilingual system is able to return one multi-faceted answer that is well-structured and precisely extracted from multiple heterogeneous healthcare sources. Further, should the seekers not be satisfied with the returned search results, our system can automatically route the unsolved questions to the professionals with relevant expertise
Measuring And Modelling The Thermal Performance Of The Tamar Suspension Bridge Using A Wireless Sensor Network, Nicholas De Battista, James M. W. Brownjohn, Hwee-Pink Tan, Ki Young Koo
Measuring And Modelling The Thermal Performance Of The Tamar Suspension Bridge Using A Wireless Sensor Network, Nicholas De Battista, James M. W. Brownjohn, Hwee-Pink Tan, Ki Young Koo
Research Collection School Of Computing and Information Systems
A study on the thermal performance of the Tamar Suspension Bridge deck in Plymouth, UK, is presented in this paper. Ambient air, suspension cable, deck and truss temperatures were acquired using a wired sensor system. Deck extension data were acquired using a two-hop wireless sensor network. Empirical models relating the deck extension to various combinations of temperatures were derived and compared. The most accurate model, which used all the four temperature variables, predicted the deck extension with an accuracy of 99.4%. Time delays ranging from 10 to 66 min were identified between the daily cycles of the air temperature and …
Running And Chasing: The Competition Between Paid Search Marketing And Search Engine Optimization, Kai Li, Mei Lin, Zhangxi Lin, Bo Xing
Running And Chasing: The Competition Between Paid Search Marketing And Search Engine Optimization, Kai Li, Mei Lin, Zhangxi Lin, Bo Xing
Research Collection School Of Computing and Information Systems
As search engine is leading the revenue growth in online marketing field, the competition of search engine marketing between paid search marketing (PSM) by search engine providers (SEPs), and search engine optimization (SEO) provided by search engine optimization firms, is white-hot. While PSM is simply for advertisers to buy the top ranks in sponsored links, SEO tries to optimize advertisers' websites by free-riding search engine's organic searching results. This study aims to investigate this competition by analytical modeling regarding organic search quality. We focus on sustainability conditions of SEO firms, investment analysis of SEO firms, and profit analysis of SEP. …
On Empirical Validation Of Compactness Measures For Electoral Redistricting And Its Significance For Application Of Models In The Social Sciences, Christine Chou, Steven O. Kimbrough, Frederic H. Murphy, John Sullivan-Fedock, C. Jason Woodard
On Empirical Validation Of Compactness Measures For Electoral Redistricting And Its Significance For Application Of Models In The Social Sciences, Christine Chou, Steven O. Kimbrough, Frederic H. Murphy, John Sullivan-Fedock, C. Jason Woodard
Research Collection School Of Computing and Information Systems
Use of optimization models in science and policy applications is often problematic because the best available models are very inaccurate representations of the originating problems. Such is the case with electoral districting models, for which there exist no generally accepted measures of compactness, in spite of many proposals and much analytical study. This article reports on an experimental investigation of subjective judgments of compactness for electoral districts. The experiment draws on a unique database of 116 distinct, legally valid districting plans for the Philadelphia City Council, discovered with evolutionary computation. Subjects in the experiment displayed, in the aggregate, remarkable agreement …
Designing Optimal Innovation Portfolio, Arcot Desai Narasimhalu
Designing Optimal Innovation Portfolio, Arcot Desai Narasimhalu
Research Collection School Of Computing and Information Systems
There have been many approaches towards investing in innovation projects. There has been very little discussion about the need to align such investments with the mission, vision, goals, leadership style, value discipline and risk appetite of an organization. This paper reviews existing approaches to innovation related investments and suggests the setting up of a proper innovation portfolio management process along with three dashboards that will help make innovation related investment decisions in an informed manner. The resulting innovation portfolio will be optimal in its alignment with an organizations mission and vision. We expect this method to be used by all …
Coupling Alignments With Recognition For Still-To-Video Face Recognition, Zhiwu Huang, X. Zhao, S. Shan, R. Wang, X. Chen
Coupling Alignments With Recognition For Still-To-Video Face Recognition, Zhiwu Huang, X. Zhao, S. Shan, R. Wang, X. Chen
Research Collection School Of Computing and Information Systems
The Still-to-Video (S2V) face recognition systems typically need to match faces in low-quality videos captured under unconstrained conditions against high quality still face images, which is very challenging because of noise, image blur, low face resolutions, varying head pose, complex lighting, and alignment difficulty. To address the problem, one solution is to select the frames of `best quality' from videos (hereinafter called quality alignment in this paper). Meanwhile, the faces in the selected frames should also be geometrically aligned to the still faces offline well-aligned in the gallery. In this paper, we discover that the interactions among the three tasks-quality …
Decision Trees To Model The Impact Of Disruption And Recovery In Supply Chain Networks, Loganathan Ponnanbalam, L. Wenbin, Xiuju Fu, Xiaofeng Yin, Zhaoxia Wang, Rick S. M. Goh
Decision Trees To Model The Impact Of Disruption And Recovery In Supply Chain Networks, Loganathan Ponnanbalam, L. Wenbin, Xiuju Fu, Xiaofeng Yin, Zhaoxia Wang, Rick S. M. Goh
Research Collection School Of Computing and Information Systems
Increase in the frequency of disruptions in the recent times and their impact have increased the attention in supply chain disruption management research. The objective of this paper is to understand as to how a disruption might affect the supply chain network - depending upon the network structure, the node that is disrupted, the disruption in production capacity of the disrupted node and the period of the disruption - via decision trees. To this end, we first developed a 5-tier agent-based supply chain model and then simulated it for various what-if disruptive scenarios for 3 different network structures (80 trials …
An Integrated Model Of Team Motivation And Worker Skills For A Computer-Based Project Management Simulation, Wee Leong Lee
An Integrated Model Of Team Motivation And Worker Skills For A Computer-Based Project Management Simulation, Wee Leong Lee
Research Collection School Of Computing and Information Systems
In this paper, I shall propose an integrated model of worker skills and team motivation for a computer-based simulation game that can be used to provide experiential learning to students. They can act as project managers here without being burdened by the costs and risks associated with unsuccessful projects. I shall present an approach of classifying skills into five different types (relevant to IT projects) and apply a five-point competency scale to each skill type. The Pearson Correlation will be applied to the scores of each skill type to generate an efficiency index that will characterize the effectiveness of a …
Factors Influencing Research Contributions And Researcher Interactions In Software Engineering: An Empirical Study, Subhajit Datta, A. S. M. Sajeev, Santonu Sarkar, Nishant Kumar
Factors Influencing Research Contributions And Researcher Interactions In Software Engineering: An Empirical Study, Subhajit Datta, A. S. M. Sajeev, Santonu Sarkar, Nishant Kumar
Research Collection School Of Computing and Information Systems
Research into software engineering (SE) education is largely concentrated on teaching and learning issues in coursework programs. This paper, in contrast, provides a meta analysis of research publications in software engineering to help with research education in SE. Studying publication patterns in a discipline will assist research students and supervisors gain a deeper understanding of how successful research has occurred in the discipline. We present results from a large scale empirical study covering over three and a half decades of software engineering research publications. We identify how different factors of publishing relate to the number of papers published as well …
Partial Least Squares Regression On Grassmannian Manifold For Emotion Recognition, M. Liu, R. Wang, Zhiwu Huang, S. Shan, X. Chen
Partial Least Squares Regression On Grassmannian Manifold For Emotion Recognition, M. Liu, R. Wang, Zhiwu Huang, S. Shan, X. Chen
Research Collection School Of Computing and Information Systems
In this paper, we propose a method for video-based human emotion recognition. For each video clip, all frames are represented as an image set, which can be modeled as a linear subspace to be embedded in Grassmannian manifold. After feature extraction, Class-specific One-to-Rest Partial Least Squares (PLS) is learned on video and audio data respectively to distinguish each class from the other confusing ones. Finally, an optimal fusion of classifiers learned from both modalities (video and audio) is conducted at decision level. Our method is evaluated on the Emotion Recognition In The Wild Challenge (EmotiW 2013). The experimental results on …
Dynamic Joint Sentiment-Topic Mode, Yulan He, Chenghua Lin, Wei Gao, Kam-Fai Wong
Dynamic Joint Sentiment-Topic Mode, Yulan He, Chenghua Lin, Wei Gao, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Social media data are produced continuously by a large and uncontrolled number of users. The dynamic nature of such data requires the sentiment and topic analysis model to be also dynamically updated, capturing the most recent language use of sentiments and topics in text. We propose a dynamic Joint Sentiment-Topic model (dJST) which allows the detection and tracking of views of current and recurrent interests and shifts in topic and sentiment. Both topic and sentiment dynamics are captured by assuming that the current sentiment-topic-specific word distributions are generated according to the word distributions at previous epochs. We study three different …
Dense Image Correspondence Under Large Appearance Variations, Linlin Liu, Kok-Lim Low, Wen-Yan Lin
Dense Image Correspondence Under Large Appearance Variations, Linlin Liu, Kok-Lim Low, Wen-Yan Lin
Research Collection School Of Computing and Information Systems
This paper addresses the difficult problem of finding dense correspondence across images with large appearance variations. Our method uses multiple feature samples at each pixel to deal with the appearance variations based on our observation that pre-defined single feature sample provides poor results in nearest neighbor matching. We apply the idea in a flow-based matching framework and utilize the best feature sample for each pixel to determine the flow field. We propose a novel energy function and use dual-layer loopy belief propagation to minimize it where the correspondence, the feature scale and rotation parameters are solved simultaneously. Our method is …
Towards A Hybrid Framework For Detecting Input Manipulation Vulnerabilities, Sun Ding, Hee Beng Kuan Tan, Lwin Khin Shar, Bindu Madhavi Padmanabhuni
Towards A Hybrid Framework For Detecting Input Manipulation Vulnerabilities, Sun Ding, Hee Beng Kuan Tan, Lwin Khin Shar, Bindu Madhavi Padmanabhuni
Research Collection School Of Computing and Information Systems
Input manipulation vulnerabilities such as SQL Injection, Cross-site scripting, Buffer Overflow vulnerabilities are highly prevalent and pose critical security risks. As a result, many methods have been proposed to apply static analysis, dynamic analysis or a combination of them, to detect such security vulnerabilities. Most of the existing methods classify vulnerabilities into safe and unsafe. They have both false-positive and false-negative cases. In general, security vulnerability can be classified into three cases: (1) provable safe, (2) provable unsafe, (3) unsure. In this paper, we propose a hybrid framework-Detecting Input Manipulation Vulnerabilities (DIMV), to verify the adequacy of security vulnerability defenses …
Adaptive Computer‐Generated Forces For Simulator‐Based Training, Expert Systems With Applications, Teck-Hou Teng, Ah-Hwee Tan, Loo-Nin Teow
Adaptive Computer‐Generated Forces For Simulator‐Based Training, Expert Systems With Applications, Teck-Hou Teng, Ah-Hwee Tan, Loo-Nin Teow
Research Collection School Of Computing and Information Systems
Simulator-based training is in constant pursuit of increasing level of realism. The transition from doctrine-driven computer-generated forces (CGF) to adaptive CGF represents one such effort. The use of doctrine-driven CGF is fraught with challenges such as modeling of complex expert knowledge and adapting to the trainees’ progress in real time. Therefore, this paper reports on how the use of adaptive CGF can overcome these challenges. Using a self-organizing neural network to implement the adaptive CGF, air combat maneuvering strategies are learned incrementally and generalized in real time. The state space and action space are extracted from the same hierarchical doctrine …
Exposing And Mitigating Privacy Loss In Crowdsourced Survey Platforms, Thivya Kandappu, Vijay Sivaraman, Arik Friedman, Roksana Borell
Exposing And Mitigating Privacy Loss In Crowdsourced Survey Platforms, Thivya Kandappu, Vijay Sivaraman, Arik Friedman, Roksana Borell
Research Collection School Of Computing and Information Systems
Crowdsourcing platforms such as Amazon Mechanical Turk and Google Consumer Surveys can profile users based on their inputs to online surveys. In this work we first demonstrate how easily user privacy can be compromised by collating information from multiple surveys. We then propose, develop, and evaluate a crowdsourcing survey platform called Loki that allows users to control their privacy loss via atsource obfuscation.
A Secure And Effective Anonymous User Authentication Scheme For Roaming Service In Global Mobility Networks, Fengtong Wen, Willy Susilo, Guomin Yang
A Secure And Effective Anonymous User Authentication Scheme For Roaming Service In Global Mobility Networks, Fengtong Wen, Willy Susilo, Guomin Yang
Research Collection School Of Computing and Information Systems
In global mobility networks, anonymous user authentication is an essential task for enabling roaming service. In a recent paper, Jiang et al. proposed a smart card based anonymous user authentication scheme for roaming service in global mobility networks. This scheme can protect user privacy and is believed to have many abilities to resist a range of network attacks, even if the secret information stored in the smart card is compromised. In this paper, we analyze the security of Jiang et al.’s scheme, and show that the scheme is in fact insecure against the stolen-verifier attack and replay attack. Then, we …
An Efficient Partial Shape Matching Algorithm For 3d Tooth Recognition, Zhiyuan Zhang, Xin Zhong, Sim Heng Ong, Kelvin W. C. Foong
An Efficient Partial Shape Matching Algorithm For 3d Tooth Recognition, Zhiyuan Zhang, Xin Zhong, Sim Heng Ong, Kelvin W. C. Foong
Research Collection School Of Computing and Information Systems
As a new biometric strategy, tooth recognition has drawn much attention in recent years. However, most existing work focus mainly on 2D dental radiographs which are less informative and vulnerable to noise and pose variance. Although there are already several attempts on 3D tooth recognition, the results are still inaccurate and performance is inefficient. Moreover, existing methods cannot recognize precisely when the post-mortem data contains incomplete teeth. In this work, we propose an efficient and accurate partial shape matching algorithm to recognize 3D teeth for human identification. Given the ante-mortem and post-mortem teeth models which were taken from patients using …
Query-Document-Dependent Fusion: A Case Study Of Multimodal Music Retrieval, Zhonghua Li, Bingjun Zhang, Yi Yu, Jialie Shen, Ye Wang
Query-Document-Dependent Fusion: A Case Study Of Multimodal Music Retrieval, Zhonghua Li, Bingjun Zhang, Yi Yu, Jialie Shen, Ye Wang
Research Collection School Of Computing and Information Systems
In recent years, multimodal fusion has emerged as a promising technology for effective multimedia retrieval. Developing the optimal fusion strategy for different modality (e.g. content, metadata) has been the subject of intensive research. Given a query, existing methods derive a unified fusion strategy for all documents with the underlying assumption that the relative significance of a modality remains the same across all documents. However, this assumption is often invalid. We thus propose a general multimodal fusion framework, query-document-dependent fusion (QDDF), which derives the optimal fusion strategy for each query-document pair via intelligent content analysis of both queries and documents. By …
An Agent-Based Simulation Approach To Experience Management In Theme Parks, Shih-Fen Cheng, Larry Junjie Lin, Jiali Du, Hoong Chuin Lau, Pradeep Reddy Varakantham
An Agent-Based Simulation Approach To Experience Management In Theme Parks, Shih-Fen Cheng, Larry Junjie Lin, Jiali Du, Hoong Chuin Lau, Pradeep Reddy Varakantham
Research Collection School Of Computing and Information Systems
In this paper, we illustrate how massive agent-based simulation can be used to investigate an exciting new application domain of experience management in theme parks, which covers topics like congestion control, incentive design, and revenue management. Since all visitors are heterogeneous and self-interested, we argue that a high-quality agent-based simulation is necessary for studying various problems related to experience management. As in most agent-base simulations, a sound understanding of micro-level behaviors is essential to construct high-quality models. To achieve this, we designed and conducted a first-of-its-kind real-world experiment that helps us understand how typical visitors behave in a theme-park environment. …
The Influence Of Online Word-Of-Mouth On Long Tail Formation, Bin Gu, Qian Tang, Andrew B. Whinston
The Influence Of Online Word-Of-Mouth On Long Tail Formation, Bin Gu, Qian Tang, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
The long tail phenomenon has been attributed to both supply side and demand side economies. While the cause on the supply side is well-known, research on the demand side has largely focused on the awareness effect of online information that helps consumers discover new and often niche products. This study expands the demand side factors by showing that online information also influences the long tail phenomenon through the informative effect, which affects consumers' evaluation of product quality. We examine the informative effect in the context of online WOM. Two sets of theories suggest opposite directions for the implication of the …
A Local Social Network Approach For Research Management, Xiaoyan Liu, Zhiling Guo, Zhenjiang Lin, Jian Ma
A Local Social Network Approach For Research Management, Xiaoyan Liu, Zhiling Guo, Zhenjiang Lin, Jian Ma
Research Collection School Of Computing and Information Systems
Traditional methods to evaluate research performance focus on citation count, quality and quantity of research output by individual researchers. These measures overlook the roles an individual plays in research collaboration, which is critical in an institutional research management environment due to the inherent interdependency among research entities. In order to address the organizational research management needs, we propose a research social network approach to better analyze local collaboration networks. For this purpose, we develop a new “collaboration supportiveness” measure to quantify an individual researcher's collaboration ability. Insights derived from this research are very helpful for managers to effectively allocate resources, …
Modeling Preferences With Availability Constraints, Bingtian Dai, Hady W. Lauw
Modeling Preferences With Availability Constraints, Bingtian Dai, Hady W. Lauw
Research Collection School Of Computing and Information Systems
User preferences are commonly learned from historical data whereby users express preferences for items, e.g., through consumption of products or services. Most work assumes that a user is not constrained in their selection of items. This assumption does not take into account the availability constraint, whereby users could only access some items, but not others. For example, in subscription-based systems, we can observe only those historical preferences on subscribed (available) items. However, the objective is to predict preferences on unsubscribed (unavailable) items, which do not appear in the historical observations due to their (lack of) availability. To model preferences in …
Improving Patient Length-Of-Stay In Emergency Department Through Dynamic Queue Management, Kar Way Tan, Hoong Chuin Lau, Francis Chun Yue Lee
Improving Patient Length-Of-Stay In Emergency Department Through Dynamic Queue Management, Kar Way Tan, Hoong Chuin Lau, Francis Chun Yue Lee
Research Collection School Of Computing and Information Systems
Addressing issue of crowding in an Emergency Department (ED) typically takes the form of process engineering or single-faceted queue management strategies such as demand restriction, queue prioritization or staffing the ED. This work provides an integrated framework to manage queue dynamically from both demand and supply perspectives. More precisely, we introduce intelligent dynamic patient prioritization strategies to manage the demand concurrently with dynamic resource adjustment policies to manage supply. Our framework allows decision-makers to select both the demand-side and supply-side strategies to suit the needs of their ED. We verify through a simulation that such a framework improves the patients' …
Fundamental Limits On End-To-End Throughput Of Network Coding In Multi-Rate And Multicast Wireless Networks, Luiz Felipe Viera, Mario Gerla, Archan Misra
Fundamental Limits On End-To-End Throughput Of Network Coding In Multi-Rate And Multicast Wireless Networks, Luiz Felipe Viera, Mario Gerla, Archan Misra
Research Collection School Of Computing and Information Systems
This paper investigates the interaction between network coding and link-layer transmission rate diversity in multi-hop wireless networks. By appropriately mixing data packets at intermediate nodes, network coding allows a single multicast flow to achieve higher throughput to a set of receivers. Broadcast applications can also exploit link-layer rate diversity, whereby individual nodes can transmit at faster rates at the expense of corresponding smaller coverage area. We first demonstrate how combining rate-diversity with network coding can provide a larger capacity for data dissemination of a single multicast flow, and how consideration of rate diversity is critical for maximizing system throughput. Next …
Modeling Temporal Adoptions Using Dynamic Matrix Factorization, Freddy Chong-Tat Chua, Richard Jayadi Oentaryo, Ee Peng Lim
Modeling Temporal Adoptions Using Dynamic Matrix Factorization, Freddy Chong-Tat Chua, Richard Jayadi Oentaryo, Ee Peng Lim
Research Collection School Of Computing and Information Systems
The problem of recommending items to users is relevant to many applications and the problem has often been solved using methods developed from Collaborative Filtering (CF). Collaborative Filtering model-based methods such as Matrix Factorization have been shown to produce good results for static rating-type data, but have not been applied to time-stamped item adoption data. In this paper, we adopted a Dynamic Matrix Factorization (DMF) technique to derive different temporal factorization models that can predict missing adoptions at different time steps in the users' adoption history. This DMF technique is an extension of the Non-negative Matrix Factorization (NMF) based on …
Firm Strategy And The Internet In U.S. Commercial Banking, Kim Huat Goh, Robert J. Kauffman
Firm Strategy And The Internet In U.S. Commercial Banking, Kim Huat Goh, Robert J. Kauffman
Research Collection School Of Computing and Information Systems
As information technology (IT) becomes more accessible, sustaining any competitive advantage from it becomes challenging. This has caused some critics to dismiss IT as a less valuable resource. We argue that, in addition to being able to generate strategic advantage, IT should also be viewed as a strategic necessity that prevents competitive disadvantage in rapidly changing business environments. We test a set of hypotheses on strategic advantage and strategic necessity in the context of Internet banking investments among the entire population of the United States Federal Deposit Insurance Corporation (FDIC) banks from 2003 to 2005. We seek to understand whether …
Topicsketch: Real-Time Bursty Topic Detection From Twitter, Wei Xie, Feida Zhu, Jing Jiang, Ee Peng Lim, Ke Wang
Topicsketch: Real-Time Bursty Topic Detection From Twitter, Wei Xie, Feida Zhu, Jing Jiang, Ee Peng Lim, Ke Wang
Research Collection School Of Computing and Information Systems
Twitter has become one of the largest platforms for users around the world to share anything happening around them with friends and beyond. A bursty topic in Twitter is one that triggers a surge of relevant tweets within a short time, which often reflects important events of mass interest. How to leverage Twitter for early detection of bursty topics has therefore become an important research problem with immense practical value. Despite the wealth of research work on topic modeling and analysis in Twitter, it remains a huge challenge to detect bursty topics in real-time. As existing methods can hardly scale …
Two Formulas For Success In Social Media: Social Learning And Network Effects, Liangfei Qiu, Qian Tang, Andrew B. Whinston
Two Formulas For Success In Social Media: Social Learning And Network Effects, Liangfei Qiu, Qian Tang, Andrew B. Whinston
Research Collection School Of Computing and Information Systems
This paper examines social learning and network effects that are particularly important for online videos, considering the limited marketing campaigns of user-generated content. Rather than combining both social learning and network effects under the umbrella of social contagion or peer influence, we develop a theoretical model and empirically identify social learning and network effects separately. Using a unique data set from YouTube, we find that both mechanisms have statistically and economically significant effects on video views, and which mechanism dominates depends on the specific video type.