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Articles 3121 - 3150 of 4492
Full-Text Articles in Entire DC Network
On Profiling Bots In Social Media, Richard J. Oentaryo, Arinto Murdopo, Philips K. Prasetyo, Ee Peng Lim
On Profiling Bots In Social Media, Richard J. Oentaryo, Arinto Murdopo, Philips K. Prasetyo, Ee Peng Lim
Research Collection School Of Computing and Information Systems
The popularity of social media platforms such as Twitter has led to the proliferation of automated bots, creating both opportunities and challenges in information dissemination, user engagements, and quality of services. Past works on profiling bots had been focused largely on malicious bots, with the assumption that these bots should be removed. In this work, however, we find many bots that are benign, and propose a new, broader categorization of bots based on their behaviors. This includes broadcast, consumption, and spam bots. To facilitate comprehensive analyses of bots and how they compare to human accounts, we develop a systematic profiling …
Landmark Reranking For Smart Travel Guide Systems By Combining And Analyzing Diverse Media, Junge Shen, Jialie Shen, Tao Mei, Xinbo Gao
Landmark Reranking For Smart Travel Guide Systems By Combining And Analyzing Diverse Media, Junge Shen, Jialie Shen, Tao Mei, Xinbo Gao
Research Collection School Of Computing and Information Systems
Advanced networking technologies and massive online social media have stimulated a booming growth of travel heterogeneous information in recent years. By employing such information, smart travel guide systems, such as landmark ranking systems, have been proposed to offer diverse online travel services. It is essential for a landmark ranking system to structure, analyze, and search the travel heterogeneous information to produce human-expected results. Therefore, currently the most fundamental yet challenging problems can be concluded: 1) how to fuse heterogeneous tourism information and 2) how to model landmark ranking. In this paper, a novel landmark search system is introduced based on …
Spiteful, One-Off, And Kind: Predicting Customer Feedback Behavior On Twitter, Agus Sulistya, Abhishek Sharma, David Lo
Spiteful, One-Off, And Kind: Predicting Customer Feedback Behavior On Twitter, Agus Sulistya, Abhishek Sharma, David Lo
Research Collection School Of Computing and Information Systems
Social media provides a convenient way for customers to express their feedback to companies. Identifying different types of customers based on their feedback behavior can help companies to maintain their customers. In this paper, we use a machine learning approach to predict a customer’s feedback behavior based on her first feedback tweet. First, we identify a few categories of customers based on their feedback frequency and the sentiment of the feedback. We identify three main categories: spiteful, one-off, and kind. Next, we build a model to predict the category of a customer given her first feedback. We use profile and …
Aspect-Based Helpfulness Prediction For Online Product Reviews, Yinfei Yang, Cen Chen, Forrest Sheng Bao
Aspect-Based Helpfulness Prediction For Online Product Reviews, Yinfei Yang, Cen Chen, Forrest Sheng Bao
Research Collection School Of Computing and Information Systems
Product reviews greatly influence purchase decisions in online shopping. A common burden of online shopping is that consumers have to search for the right answers through massive reviews, especially on popular products. Hence, estimating and predicting the helpfulness of reviews become important tasks to directly improve shopping experience. In this paper, we propose a new approach to helpfulness prediction by leveraging aspect analysis of reviews. Our hypothesis is that a helpful review will cover many aspects of a product at different emphasis levels. The first step to tackle this problem is to extract proper aspects. Because related products share common …
Fundamentals Of Machine Learning For Neural Machine Translation, John D. Kelleher
Fundamentals Of Machine Learning For Neural Machine Translation, John D. Kelleher
Conference papers
This paper presents a short introduction to neural networks and how they are used for machine translation and concludes with some discussion on the current research challenges being addressed by neural machine translation (NMT) research. The primary goal of this paper is to give a no-tears introduction to NMT to readers that do not have a computer science or mathematical background. The secondary goal is to provide the reader with a deep enough understanding of NMT that they can appreciate the strengths of weaknesses of the technology. The paper starts with a brief introduction to standard feed-forward neural networks (what …
Cover Text Steganography: N-Gram And Entropy-Based Approach, Sara M. Rico-Larmer
Cover Text Steganography: N-Gram And Entropy-Based Approach, Sara M. Rico-Larmer
KSU Proceedings on Cybersecurity Education, Research and Practice
Steganography is an ancient technique for hiding a secret message within ordinary looking messages or objects (e.g., images), also known as cover messages. Among various techniques, hiding text data in plain text file is a challenging task due to lack of redundant information. This paper proposes two new approaches to embed a secret message in a cover text document. The two approaches are n-gram and entropy metric-based generation of stego text. We provide examples of encoding secret messages in a cover text document followed by an initial evaluation of how well stego texts look close to the plain …
The Role Of Perception In Situated Spatial Reference, John D. Kelleher
The Role Of Perception In Situated Spatial Reference, John D. Kelleher
Conference papers
This position paper set out the argument that an interesting avenue of exploration and study of universals and variation in spatial reference is to address this topic in termsa of the universals in human perception and attention and to explore how these universals impact on spatial reference across cultures and languages.
Mining Mixed-Initiative Dialogs, Saverio Perugini
Mining Mixed-Initiative Dialogs, Saverio Perugini
Computer Science Faculty Publications
Human-computer dialogs are an important vehicle through which to produce a rich and compelling form of human-computer interaction. We view the specification of a human-computer dialog as a set of sequences of progressive interactions between a user and a computer system, and mine partially ordered sets, which correspond to mixing dialog initiative, embedded in these sets of sequences—a process we refer to as dialog mining—because partially ordered sets can be advantageously exploited to reduce the control complexity of a dialog implementation. Our mining losslessly compresses the specification of a dialog. We describe our mining algorithm and report the results of …
Development And Semantic Exploitation Of A Relational Data Model For Service Delivery In South African Municipalities, Kgotatso Desmond Mogotlane, Jean Vincent Fonou Dombeu
Development And Semantic Exploitation Of A Relational Data Model For Service Delivery In South African Municipalities, Kgotatso Desmond Mogotlane, Jean Vincent Fonou Dombeu
The African Journal of Information Systems
Relational databases (RDB) are the main sources of structured data for government institutions and businesses. Since these databases are dependent on autonomous hardware and software they create problems of data integration and interoperability. Solutions have been proposed to convert RDB into ontology to enable their sharing, reuse and integration on the Semantic Web. However, the proposed methods and techniques remain highly technical and there is lack of research that focuses on the empirical application of these methods and techniques in information systems (IS) domains. This study develops and semantically exploits a relational data model of the South African Municipalities Information …
Tracking Virality And Susceptibility In Social Media, Tuan Anh Hoang, Ee-Peng Lim
Tracking Virality And Susceptibility In Social Media, Tuan Anh Hoang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
In social media, the magnitude of information propagation hinges on the virality and susceptibility of users spreading and receiving the information respectively, as well as the virality of information items. These users' and items' behavioral factors evolve dynamically at the same time interacting with one another. Previous works however measure the factors statically and independently in a restricted case: each user has only a single adoption on each item, and/or users' exposure to items are observable. In this work, we investigate the inter-relationship among the factors and users' multiple adoptions on items to propose both new static and temporal models …
Table Of Contents
Journal of Digital Forensics, Security and Law
No abstract provided.
Special Issue On Cyberharassment Investigation: Advances And Trends, Joanne Bryce, Virginia N. L. Franqueira, Andrew Marrington
Special Issue On Cyberharassment Investigation: Advances And Trends, Joanne Bryce, Virginia N. L. Franqueira, Andrew Marrington
Journal of Digital Forensics, Security and Law
Empirical and anecdotal evidence indicates that cyberharassment is more prevalent as the use of social media becomes increasingly widespread, making geography and physical proximity irrelevant. Cyberharassment can take different forms (e.g., cyberbullying, cyberstalking, cybertrolling), and be motivated by the objectives of inflicting distress, exercising control, impersonation, and defamation. Little is currently known about the modus operandi of offenders and their psychological characteristics. Investigation of these behaviours is particularly challenging because it involves digital evidence distributed across the devices of both alleged offenders and victims, as well as online service providers, sometimes over an extended period of time. This special issue …
Toward Online Linguistic Surveillance Of Threatening Messages, Brian H. Spitzberg, Jean Mark Gawron
Toward Online Linguistic Surveillance Of Threatening Messages, Brian H. Spitzberg, Jean Mark Gawron
Journal of Digital Forensics, Security and Law
Threats are communicative acts, but it is not always obvious what they communicate or when they communicate imminent credible and serious risk. This paper proposes a research- and theory-based set of over 20 potential linguistic risk indicators that may discriminate credible from non-credible threats within online threat message corpora. Two prongs are proposed: (1) Using expert and layperson ratings to validate subjective scales in relation to annotated known risk messages, and (2) Using the resulting annotated corpora for automated machine learning with computational linguistic analyses to classify non-threats, false threats, and credible threats. Rating scales are proposed, existing threat corpora …
Preliminaries To A Study Of Stance In News Broadcasts, Nigel Ward
Preliminaries To A Study Of Stance In News Broadcasts, Nigel Ward
Departmental Technical Reports (CS)
Aspects of stance have significant potential for information retrieval and filtering. This technical report is about stance in radio news broadcast, and is intended primarily to motivate and document details of the data and annotations used in the work reported in Inferring Stance from Prosody (Ward et al., 2016). It describes the process of identifying 14 important aspects of stance, describes two corpora for investigating stance, describes the annotation of those corpora, presents some preliminary observations, and lists a set of useful prosodic features.
Extracting Food Substitutes From Food Diary Via Distributional Similarity, Palakorn Achananuparp, Ingmar Weber
Extracting Food Substitutes From Food Diary Via Distributional Similarity, Palakorn Achananuparp, Ingmar Weber
Research Collection School Of Computing and Information Systems
In this paper, we explore the problem of identifying substitute relationship between food pairs from real-world food consumption data as the first step towards the healthier food recommendation. Our method is inspired by the distributional hypothesis in linguistics. Specifically, we assume that foods that are consumed in similar contexts are more likely to be similar dietarily. For example, a turkey sandwich can be considered a suitable substitute for a chicken sandwich if both tend to be consumed with french fries and salad. To evaluate our method, we constructed a real-world food consumption dataset from MyFitnessPal's public food diary entries and …
Microblogging Content Propagation Modeling Using Topic-Specific Behavioral Factors, Tuan Anh Hoang, Ee-Peng Lim
Microblogging Content Propagation Modeling Using Topic-Specific Behavioral Factors, Tuan Anh Hoang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
When a microblogging user adopts some content propagated to her, we can attribute that to three behavioral factors, namely, topic virality, user virality, and user susceptibility. Topic virality measures the degree to which a topic attracts propagations by users. User virality and susceptibility refer to the ability of a user to propagate content to other users, and the propensity of a user adopting content propagated to her, respectively. In this paper, we study the problem of mining these behavioral factors specific to topics from microblogging content propagation data. We first construct a three dimensional tensor for representing the propagation instances. …
When A Friend Online Is More Than A Friend In Life: Intimate Relationship Prediction In Microblogs, Yunshi Lan, Mengqi Zhang, Feida Zhu, Jing Jiang, Ee-Peng Lim
When A Friend Online Is More Than A Friend In Life: Intimate Relationship Prediction In Microblogs, Yunshi Lan, Mengqi Zhang, Feida Zhu, Jing Jiang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Microblogging services such as Twitter and Sina Weibo have been an important, if not indespensible, platform for people around the world to connect to one another. The rich content and user interactions on these platforms reveal insightful information about each user that are valuable for various real-life applications. In particular, user offline relationships, especially those intimate ones such as family members and couples, offer distinctive value for many business and social settings. In this study, we focus on using Sina Weibo to discover intimate offline relationships among users. The problem is uniquely interesting and challenging due to the difficulty in …
Towards A Deep Learning-Based Activity Discovery System, Eoin Rogers, John D. Kelleher, Robert J. Ross
Towards A Deep Learning-Based Activity Discovery System, Eoin Rogers, John D. Kelleher, Robert J. Ross
Conference papers
Activity discovery is a challenging machine learning problem where we seek to uncover new or altered behavioural patterns in sensor data. In this paper we motivate and introduce a novel approach to activity discovery based on modern deep learning techniques. We hypothesise that our proposed approach can deal with interleaved datasets in a more intelligent manner than most existing AD methods. We also build upon prior work building hierarchies of activities that capture the inherent ag- gregate nature of complex activities and show how this could plausibly be adapted to work with the deep learning technique we present. Finally, we …
Representations And Models For Large-Scale Video Understanding, Du Le Hong Tran
Representations And Models For Large-Scale Video Understanding, Du Le Hong Tran
Dartmouth College Ph.D Dissertations
In this thesis, we investigate different representations and models for large-scale video understanding. These methods include a mid-level representation for action recognition, a deep-learned representation for video analysis, a generic convolutional network architecture for video voxel prediction, and a new high-level task and benchmark of video comprehension. First, we present EXMOVES, a mid-level representation for scalable action recognition. The entries in EXMOVES representation are the calibrated outputs of a set of movement classifiers over spatial-temporal volumes of the input video. Each movement classifier is a simple exemplar-SVM trained on low-level features. Our EXMOVES requires a minimal amount of supervision while …
Topic Extraction From Microblog Posts Using Conversation Structures, Jing Li, Ming Liao, Wei Gao, Yulan He, Kam-Fai Wong
Topic Extraction From Microblog Posts Using Conversation Structures, Jing Li, Ming Liao, Wei Gao, Yulan He, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Conventional topic models are ineffective for topic extraction from microblog messages since the lack of structure and context among the posts renders poor message-level word co-occurrence patterns. In this work, we organize microblog posts as conversation trees based on reposting and replying relations, which enrich context information to alleviate data sparseness. Our model generates words according to topic dependencies derived from the conversation structures. In specific, we differentiate messages as leader messages, which initiate key aspects of previously focused topics or shift the focus to different topics, and follower messages that do not introduce any new information but simply echo …
Profiling Social Media Users With Selective Self-Disclosure Behavior, Wei Gong
Profiling Social Media Users With Selective Self-Disclosure Behavior, Wei Gong
Dissertations and Theses Collection
Social media has become a popular platform for millions of users to share activities and thoughts. Many applications are now tapping on social media to disseminate information (e.g., news), to promote products (e.g., advertisements), to manage customer relationship (e.g., customer feedback), and to source for investment (e.g., crowdfunding). Many of these applications require user profile knowledge to select the target social media users or to personalize messages to users. Social media user profiling is a task of constructing user profiles such as demographical labels, interests, and opinions, etc., using social media data. Among the social media user profiling research works, …
Analyzing Clinical Depressive Symptoms In Twitter, Amir Hossein Yazdavar, Hussein S. Al-Olimat, Tanvi Banerjee, Krishnaprasad Thirunarayan, Amit P. Sheth
Analyzing Clinical Depressive Symptoms In Twitter, Amir Hossein Yazdavar, Hussein S. Al-Olimat, Tanvi Banerjee, Krishnaprasad Thirunarayan, Amit P. Sheth
Kno.e.sis Publications
350 million people are suffering from clinical depression worldwide.
The Phraseworthy App, Dallin D. Oaks
The Phraseworthy App, Dallin D. Oaks
BYU Research Development Office Research Networking Conference
Brainstorming software that provides ideas about potential word plays for headlines, slogans, product names, titles, and more.
Anti-Forensics: Furthering Digital Forensic Science Through A New Extended, Granular Taxonomy, Kevin Conlan, Ibrahim Baggili, Frank Breitinger
Anti-Forensics: Furthering Digital Forensic Science Through A New Extended, Granular Taxonomy, Kevin Conlan, Ibrahim Baggili, Frank Breitinger
Electrical & Computer Engineering and Computer Science Faculty Publications
Anti-forensic tools, techniques and methods are becoming a formidable obstacle for the digital forensic community. Thus, new research initiatives and strategies must be formulated to address this growing problem. In this work we first collect and categorize 308 antidigital forensic tools to survey the field. We then devise an extended anti-forensic taxonomy to the one proposed by Rogers (2006) in order to create a more comprehensive taxonomy and facilitate linguistic standardization. Our work also takes into consideration anti-forensic activity which utilizes tools that were not originally designed for antiforensic purposes, but can still be used with malicious intent. This category …
A Classification Of Representable T-Norm Operators For Picture Fuzzy Sets, Bui Cong Cuong, Vladik Kreinovich, Roan Thi Ngan
A Classification Of Representable T-Norm Operators For Picture Fuzzy Sets, Bui Cong Cuong, Vladik Kreinovich, Roan Thi Ngan
Departmental Technical Reports (CS)
T-norms and t-conorms are basic operators of fuzzy logics. The classifications of these operators are significant problems. Some results of the classifications of fuzzy logics operators for fuzzy sets are known. In 2013, we defined the picture fuzzy sets, and in 2015 some representable t-norms operators and t-conorms operators were defined. In this paper, we investigate the classification of representable picture t-norms and picture t-conorms operators for picture fuzzy sets.
Concepts Of Solutions Of Uncertain Equations With Intervals, Probabilities And Fuzzy Sets For Applied Tasks, Boris Kovalerchuk, Vladik Kreinovich
Concepts Of Solutions Of Uncertain Equations With Intervals, Probabilities And Fuzzy Sets For Applied Tasks, Boris Kovalerchuk, Vladik Kreinovich
Departmental Technical Reports (CS)
The focus of this paper is to clarify the concepts of solutions of linear equations in interval, probabilistic, and fuzzy sets setting for real world tasks. There is a fundamental difference between formal definitions of the solutions and physically meaningful concepts of solution in applied tasks, when equations have uncertain components. For instance, a formal definition of the solution in terms of Moore interval analysis can be completely irrelevant for solving a real world task. We show that formal definitions must follow a meaningful concept of the solution in the real world. The paper proposed several formalized definitions of the …
Stylometry With R: A Package For Computational Text Analysis, Maciej Eder, Jan Rybicki, Mike Kestemont
Stylometry With R: A Package For Computational Text Analysis, Maciej Eder, Jan Rybicki, Mike Kestemont
The R Journal
This software paper describes ‘Stylometry with R’ (stylo), a flexible R package for the high level analysis of writing style in stylometry. Stylometry (computational stylistics) is concerned with the quantitative study of writing style, e.g. authorship verification, an application which has considerable potential in forensic contexts, as well as historical research. In this paper we introduce the possibilities of stylo for computational text analysis, via a number of dummy case studies from English and French literature. We demonstrate how the package is particularly useful in the exploratory statistical analysis of texts, e.g. with respect to authorial writing style. …
Tool Comparison Of Semantic Parsers, Robert Hinh
Tool Comparison Of Semantic Parsers, Robert Hinh
Open Access Theses
Natural Language Processing (NLP) is a vital aspect for artificial intelligence systems to achieve integration into human lives, which has been a goal for researchers in this industry. While NLP focuses on an array of problems, semantic parsing will be specifically focused on throughout this paper. These parsers have been considerably targeted for improvement through the scientific community and demand for semantic parsers that achieve high accuracy has increased. There have been many approaches developed for this specific purpose and in this paper, a deep analysis was performed to compare the performance of semantic parsing systems. The implications of this …