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Articles 1141 - 1170 of 1692
Full-Text Articles in Entire DC Network
Cross-Border M&A: Challenges And Opportunities In Global Business Environment [Guest Editors' Introduction], Rosa Caizza, Katsuhiko Shimizu, Toru Yoshikawa
Cross-Border M&A: Challenges And Opportunities In Global Business Environment [Guest Editors' Introduction], Rosa Caizza, Katsuhiko Shimizu, Toru Yoshikawa
Research Collection Lee Kong Chian School of Business
Under a rapidly changing and globalizing environment, mergers and acquisitions (M&As) have become one of the most important strategic initiatives. In this context, cross-border M&As provide various opportunities and benefits such as expeditious entry into new markets by gaining local knowledge, supplier networks, government relationships, and customers embedded in the target firm.
Inferring User Consumption Preferences From Social Media, Yang Li, Jing Jiang, Ting Liu
Inferring User Consumption Preferences From Social Media, Yang Li, Jing Jiang, Ting Liu
Research Collection School Of Computing and Information Systems
Social Media has already become a new arena of our lives and involved different aspects of our social presence. Users' personal information and activities on social media presumably reveal their personal interests, which offer great opportunities for many e-commerce applications. In this paper, we propose a principled latent variable model to infer user consumption preferences at the category level (e.g. inferring what categories of products a user would like to buy). Our model naturally links users' published content and following relations on microblogs with their consumption behaviors on e-commerce websites. Experimental results show our model outperforms the state-of-the-art methods significantly …
Recurrent Neural Networks With Auxiliary Labels For Cross-Domain Opinion Target Extraction, Ying Ding, Jianfei Yu, Jing Jiang
Recurrent Neural Networks With Auxiliary Labels For Cross-Domain Opinion Target Extraction, Ying Ding, Jianfei Yu, Jing Jiang
Research Collection School Of Computing and Information Systems
Opinion target extraction is a fundamental task in opinion mining. In recent years, neural network based supervised learning methods have achieved competitive performance on this task. However, as with any supervised learning method, neural network based methods for this task cannot work well when the training data comes from a different domain than the test data. On the other hand, some rule-based unsupervised methods have shown to be robust when applied to different domains. In this work, we use rule-based unsupervised methods to create auxiliary labels and use neural network models to learn a hidden representation that works well for …
No-Place, New Places: Death And Its Rituals In Urban Asia, Lily Kong
No-Place, New Places: Death And Its Rituals In Urban Asia, Lily Kong
Research Collection School of Social Sciences
In many Asian cities, particularly those that confront increasing land scarcity, the conversion from burial to cremation has been encouraged by state agencies in the last several decades. From Hong Kong to Seoul to Singapore, planning agencies have sought to reduce the use of space for the dead, in order to release land for the use of the living. More secular guiding principles regarding efficient land use in these cities had originally come up against the symbolic values invested in burial spaces, resulting in conflicts between different value systems. In more recent years, however, the shift to cremation and columbaria …
Are All Interferences Bad? Bilingual Advantages In Working Memory Are Modulated By Varying Demands For Controlled Processing, Hwajin Yang, Sujin Yang
Are All Interferences Bad? Bilingual Advantages In Working Memory Are Modulated By Varying Demands For Controlled Processing, Hwajin Yang, Sujin Yang
Research Collection School of Social Sciences
We investigated bilingual advantages in general control abilities using three complex-span tasks of working memory (WM). An operation-span task served as a baseline measure of WM capacity. Additionally, two modified versions of the Stroop-span task were designed to place varying attentional-control demands during memoranda encoding by asking participants either to read the to-be-remembered item aloud (lower cognitive control; i.e., Stroop-span task) or to name the font color of the to-be-remembered item while still encoding the word for later recall (greater cognitive control; i.e., attention-impeded Stroop-span task). Twenty-six Korean-English bilinguals and 25 English-native monolinguals were tested. We found that bilinguals outperformed …
The Habits Of Highly Effective Researchers: An Empirical Study, Subhajit Datta, Partha Basuchowdhuri, Surajit Acharya, Subhashis Majumder
The Habits Of Highly Effective Researchers: An Empirical Study, Subhajit Datta, Partha Basuchowdhuri, Surajit Acharya, Subhashis Majumder
Research Collection School Of Computing and Information Systems
Interest in the habits of influential individuals cuts across domains. As researchers, we are intrigued why few attain significant eminence in their fields, whereas many operate in obscurity. An empirical examination of this question has been made possible by the recent availability of large scale publication data. In this paper, we use information from the AMiner Paper Citation and Author Collaboration Networks to discern factors that relate to the impact of influential researchers across five domains in the computing discipline. We propose and apply a novel algorithm to identify influential vertices in co-authorship networks built from total corpora of 1,00,000+papers …
Fine-Grained Sentiment Analysis Of Social Media With Emotion Sensing, Zhaoxia Wang, Chee Seng Chong, Landy Lan, Yinping Yang, Beng-Seng Ho, Joo Chuan Tong
Fine-Grained Sentiment Analysis Of Social Media With Emotion Sensing, Zhaoxia Wang, Chee Seng Chong, Landy Lan, Yinping Yang, Beng-Seng Ho, Joo Chuan Tong
Research Collection School Of Computing and Information Systems
Social media is arguably the richest source of human generated text input. Opinions, feedbacks and critiques provided by internet users reflect attitudes and sentiments towards certain topics, products, or services. The sheer volume of such information makes it effectively impossible for any group of persons to read through. Thus, social media sentiment analysis has become an important area of work to make sense of the social media talk. However, most existing sentiment analysis techniques focus only on the aggregate level, classifying sentiments broadly into positive, neutral or negative, and lack the capabilities to perform fine-grained sentiment analysis. This paper describes …
Online Hacker Forum Censorship: Would Banning The Bad Guys Attract Good Guys?, Qiu-Hong Wang, Le-Ting Zhang, Meng-Ke Qiao
Online Hacker Forum Censorship: Would Banning The Bad Guys Attract Good Guys?, Qiu-Hong Wang, Le-Ting Zhang, Meng-Ke Qiao
Research Collection School Of Computing and Information Systems
To tackle the ubiquitous cybersecurity threats, a few countries have enacted legislation to criminalize the production, distribution and possession of computer misuse tools. Consequently, online hacker forums, which enable the provision and dissemination of malicious cyber-attack techniques among potential hackers or technology-savvy users, are subject to censorship. This project examines the mixed impacts of online hacker forum censorship on users’ contribution to protection discussion through a natural experiment with large-scale content analysis. We find that while the enforcement indeed reduced the discussion on malicious cyber-attacks, the discussion on cybersecurity protection could increase or decrease in different scenarios. The rationale is …
Research Strategies For Biomedical And Health Informatics: Some Thought-Provoking And Critical Proposals To Encourage Scientific Debate On The Nature Of Good Research In Medical Informatics, Reinhold Haux, Et Al.
Research Strategies For Biomedical And Health Informatics: Some Thought-Provoking And Critical Proposals To Encourage Scientific Debate On The Nature Of Good Research In Medical Informatics, Reinhold Haux, Et Al.
Research Collection School Of Computing and Information Systems
Medical informatics, or biomedical and health informatics (BMHI), has become an established scientific discipline. In all such disciplines there is a certain inertia to persist in focusing on well-established research areas and to hold on to well-known research methodologies rather than adopting new ones, which may be more appropriate. To search for answers to the following questions: What are research fields in informatics, which are not being currently adequately addressed, and which methodological approaches might be insufficiently used? Do we know about reasons? What could be consequences of change for research and for education? Outstanding informatics scientists were invited to …
Pairwise Relation Classification With Mirror Instances And A Combined Convolutional Neural Network, Jianfei Yu, Jing Jiang
Pairwise Relation Classification With Mirror Instances And A Combined Convolutional Neural Network, Jianfei Yu, Jing Jiang
Research Collection School Of Computing and Information Systems
Relation classification is the task of classifying the semantic relations between entity pairs in text. Observing that existing work has not fully explored using different representations for relation instances, especially in order to better handle the asymmetry of relation types, in this paper, we propose a neural network based method for relation classification that combines the raw sequence and the shortest dependency path representations of relation instances and uses mirror instances to perform pairwise relation classification. We evaluate our proposed models on two widely used datasets: SemEval-2010 Task 8 and ACE-2005. The empirical results show that our combined model together …
Hashtag Recommendation With Topical Attention-Based Lstm, Yang Li, Ting Liu, Jing Jiang, Liang Zhang
Hashtag Recommendation With Topical Attention-Based Lstm, Yang Li, Ting Liu, Jing Jiang, Liang Zhang
Research Collection School Of Computing and Information Systems
Microblogging services allow users to create hashtags to categorize their posts. In recent years,the task of recommending hashtags for microblogs has been given increasing attention. However,most of existing methods depend on hand-crafted features. Motivated by the successful use oflong short-term memory (LSTM) for many natural language processing tasks, in this paper, weadopt LSTM to learn the representation of a microblog post. Observing that hashtags indicatethe primary topics of microblog posts, we propose a novel attention-based LSTM model whichincorporates topic modeling into the LSTM architecture through an attention mechanism. Weevaluate our model using a large real-world dataset. Experimental results show that …
Domain Identification For Intention Posts On Online Social Media, Thai Le Luong, Quoc Tuan Truong, Hai-Trieu Dang, Xuan Hieu Phan
Domain Identification For Intention Posts On Online Social Media, Thai Le Luong, Quoc Tuan Truong, Hai-Trieu Dang, Xuan Hieu Phan
Research Collection School Of Computing and Information Systems
Today, more and more Internet users are willing to share their feeling, activities, and even their intention about what they plan to do on online social media. We can easily see posts like "I plan to buy an apartment this year", or "We are looking for a tour for 3 people to Nha Trang" on online forums or social networks. Recognizing those user intents on online social media is really useful for targeted advertising. However fully understanding user intents is a complicated and challenging process which includes three major stages: user intent filtering, intent domain identification, and intent parsing and …
Lexicon Knowledge Extraction With Sentiment Polarity Computation, Zhaoxia Wang, Vincent Joo Chuan Tong, Pingcheng Ruan, Fang Li
Lexicon Knowledge Extraction With Sentiment Polarity Computation, Zhaoxia Wang, Vincent Joo Chuan Tong, Pingcheng Ruan, Fang Li
Research Collection School Of Computing and Information Systems
Sentiment analysis is one of the most popular natural language processing techniques. It aims to identify the sentiment polarity (positive, negative, neutral or mixed) within a given text. The proper lexicon knowledge is very important for the lexicon-based sentiment analysis methods since they hinge on using the polarity of the lexical item to determine a text's sentiment polarity. However, it is quite common that some lexical items appear positive in the text of one domain but appear negative in another. In this paper, we propose an innovative knowledge building algorithm to extract sentiment lexicon knowledge through computing their polarity value …
The Cultural Pragmatics Of Political Apology, Hiro Saito
The Cultural Pragmatics Of Political Apology, Hiro Saito
Research Collection School of Social Sciences
In recent decades, research on ‘political apology’, wherein the state apologizes to victims of its past wrongs, has multiplied, as redress movements based on human rights have proliferated around the world. Since most of this research has been conducted by political philosophers, however, analyses of political apologies tend to adopt formal and normative perspectives. To propose an alternative, empirically-grounded approach, in this paper, I develop the ‘cultural pragmatics’ of political apology. To this end, I first conceptualize political apology as a social performance aimed to ‘re-fuse’ an impaired relationship between the perpetrator state and the victim individual. This conceptual move …
Social Media And Political Communication In The 2014 Elections To The European Parliament, Paul Nulty, Yannis Theocharis, Sebastian Adrian Popa, Olivier Parnet, Kenneth Benoit
Social Media And Political Communication In The 2014 Elections To The European Parliament, Paul Nulty, Yannis Theocharis, Sebastian Adrian Popa, Olivier Parnet, Kenneth Benoit
Research Collection School of Social Sciences
Social media play an increasingly important part in the communication strategies of political campaigns by reflecting information about the policy preferences and opinions of political actors and their public followers. In addition, the content of the messages provides rich information about the political issues and the framing of those issues during elections, such as whether contested issues concern Europe or rather extend pre-existing national debates. In this study, we survey the European landscape of social media using tweets originating from and referring to political actors during the 2014 European Parliament election campaign. We describe the language and national distribution of …
An Agent-Based Approach To Human Migration Movement, Larry Lin, Kathleen M. Carley, Shih-Fen Cheng
An Agent-Based Approach To Human Migration Movement, Larry Lin, Kathleen M. Carley, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
How are the populations of the world likely to shift? Which countries will be impacted by sea-level rise? This paper uses a country-level agent-based dynamic network model to examine shifts in population given network relations among countries, which influences overall population change. Some of the networks considered include: alliance networks, shared language networks, economic influence networks, and proximity networks. Validation of model is done for migration probabilities between countries, as well as for country populations and distributions. The proposed framework provides a way to explore the interaction between climate change and policy factors at a global scale.
From Context To Text In Contractual Interpretation: Is There Really A Problem With The Plain Meaning Rule?, Yihan Goh
Research Collection Yong Pung How School Of Law
Much of the contemporary scholarship on contractual interpretation is staunchly against a textual analysis, by which a court can only depart from the plain meaning of a contract exceptionally. It is therefore no surprise that scholars have reacted negatively to the spate of recent cases where the English courts have re-emphasized the plain meaning of the text in contractual interpretation. Yet one cannot help but wonder whether a textual analysis is really so problematic when courts across the common law world have re-embraced it. Drawing from both theoretical and comparative perspectives, this paper suggests that a focus on the text …
Learning Sentence Embeddings With Auxiliary Tasks For Cross-Domain Sentiment Classification, Jianfei Yu, Jing Jiang
Learning Sentence Embeddings With Auxiliary Tasks For Cross-Domain Sentiment Classification, Jianfei Yu, Jing Jiang
Research Collection School Of Computing and Information Systems
In this paper, we study cross-domain sentiment classification with neural network architectures. We borrow the idea from Structural Correspondence Learning and use two auxiliary tasks to help induce a sentence embedding that supposedly works well across domains for sentiment classification. We also propose to jointly learn this sentence embedding together with the sentiment classifier itself. Experiment results demonstrate that our proposed joint model outperforms several state-of-the-art methods on five benchmark datasets.
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 …
’A Beautiful Bridge’: Chinese Indonesian Associations, Social Capital And Strategic Identification In A New Era Of China Indonesia Relations, Charlotte Setijadi
’A Beautiful Bridge’: Chinese Indonesian Associations, Social Capital And Strategic Identification In A New Era Of China Indonesia Relations, Charlotte Setijadi
Research Collection School of Social Sciences
In Indonesia, Chinese voluntary associations took on a new level of importance after the fall of Suharto’s New Order regime in 1998 that ushered in a revival of Chinese identity politics. At the same time, Sino-Indonesian relations are blossoming, and the rise of China as a global power means that Indonesia can only benefit from stronger ties with China in the future. In this new atmosphere of cooperation, I argue that Chinese Indonesian individuals and voluntary organizations play a crucial function as trade and cultural intermediaries. Drawing on both empirical and qualitative fieldwork data, in this paper, I examine how …
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 …
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 …
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 …
The Too-Much Precision Effect: When And Why Precise Anchors Backfire With Experts, David D. Loschelder, Malte Friese, Michael Schaerer, Adam D. Galinsky
The Too-Much Precision Effect: When And Why Precise Anchors Backfire With Experts, David D. Loschelder, Malte Friese, Michael Schaerer, Adam D. Galinsky
Research Collection Lee Kong Chian School Of Business
Past research has suggested a fundamental principle of price precision: The more precise an opening price, the more it anchors counteroffers. The present research challenges this principle by demonstrating a too-much-precision effect. Five experiments (involving 1,320 experts and amateurs in real-estate, jewelry, car, and human-resources negotiations) showed that increasing the precision of an opening offer had positive linear effects for amateurs but inverted-U-shaped effects for experts. Anchor precision backfired because experts saw too much precision as reflecting a lack of competence. This negative effect held unless first movers gave rationales that boosted experts’ perception of their competence. Statistical mediation and …
Conceptual Representation Changes In Indonesian-English Bilinguals, Andree Hartanto, Lidia Suarez
Conceptual Representation Changes In Indonesian-English Bilinguals, Andree Hartanto, Lidia Suarez
Research Collection School of Social Sciences
This study investigated conceptual representations changes in bilinguals. Participants were Indonesian-English bilinguals (dominant in Indonesian, with different levels of English proficiency) and a control group composed of English-dominant bilinguals. All completed a gender decision task, in which participants decided whether English words referred to a male or female person or animal. In order to explore conceptual representations, we divided the words into gender-specific and gender-ambiguous words. Gender-specific words were words in which conceptual representations contained gender as a defining feature, in both English and Indonesian (e.g., uncle). In contrast, gender-ambiguous words were words in which gender was a defining feature …
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 …
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 …
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. …
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 …