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Social and Behavioral Sciences Commons™
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- Social media (4)
- Social network (3)
- Machine learning (2)
- Adoption dynamics (1)
- Algorithm (1)
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- Anomalous behavior (1)
- Anomaly detection (1)
- Brand factors (1)
- Bursty topic detection (1)
- Classification (1)
- Collective anomaly (1)
- Correlation (1)
- Craussian process (1)
- Data analytics (1)
- Data mining (1)
- Data utility (1)
- Diffusion (1)
- Entity linking (1)
- Evaluation (1)
- Event detection (1)
- Event identification (1)
- Event summarization (1)
- Experimentation (1)
- Framework (1)
- Game theory (1)
- Geospatial (1)
- Graph anomaly (1)
- Graphical models (1)
- Household hazardous waste (1)
- Impact (1)
Articles 1 - 15 of 15
Full-Text Articles in Social and Behavioral Sciences
Context Recovery In Location-Based Social Networks, Wen Haw Chong
Context Recovery In Location-Based Social Networks, Wen Haw Chong
Dissertations and Theses Collection (Open Access)
This dissertation addresses context recovery in Location-Based Social Networks (LBSN), which are platforms where users post content from various locations. With this general LBSN definition, many existing social media platforms that support user-generated location relevant content using mobile devices could also qualify as LBSNs. Context recovery for such user posts refers to recovering the venue and the semantic contexts of these user posts. Such information is useful for user profiling and to support various applications such as venue recommendation and location- based advertising.
Policy Analytics For Environmental Sustainability: Household Hazardous Waste And Water Impacts Of Carbon Pollution Standards, Kustini
Dissertations and Theses Collection (Open Access)
Policy analytics are essential in supporting more informed policy-making in environmental management. This dissertation employs a fusion of machine methods and explanatory empiricism that involves data analytics, math programming, optimization, econometrics, geospatial and spatiotemporal analysis, and other approaches for assessing and evaluating current and future environmental policies.
Essay 1 discusses household informedness and its impact on the collection and recycling of household hazardous waste (HHW). Household informedness is the degree to which households have the necessary information to make utility-maximizing decisions about the handling of their waste. Such informedness seems to be influenced by HHW public education and environmental quality …
An Integrated Framework For Modeling And Predicting Spatiotemporal Phenomena In Urban Environments, Tuc Viet Le
An Integrated Framework For Modeling And Predicting Spatiotemporal Phenomena In Urban Environments, Tuc Viet Le
Dissertations and Theses Collection (Open Access)
This thesis proposes a general solution framework that integrates methods in machine learning in creative ways to solve a diverse set of problems arising in urban environments. It particularly focuses on modeling spatiotemporal data for the purpose of predicting urban phenomena. Concretely, the framework is applied to solve three specific real-world problems: human mobility prediction, trac speed prediction and incident prediction. For human mobility prediction, I use visitor trajectories collected a large theme park in Singapore as a simplified microcosm of an urban area. A trajectory is an ordered sequence of attraction visits and corresponding timestamps produced by a visitor. …
Modeling Adoption Dynamics In Social Networks, Minh Duc Luu
Modeling Adoption Dynamics In Social Networks, Minh Duc Luu
Dissertations and Theses Collection
This dissertation studies the modeling of user-item adoption dynamics where an item can be an innovation, a piece of contagious information or a product. By “adoption dynamics” we refer to the process of users making decision choices to adopt items based on a variety of user and item factors. In the context of social networks, “adoption dynamics” is closely related to “item diffusion”. When a user in a social network adopts an item, she may influence her network neighbors to adopt the item. Those neighbors of her who adopt the item then continue to trigger more adoptions. As this progress …
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, …
User Behavior Mining In Microblogging, Tuan Anh Hoang
User Behavior Mining In Microblogging, Tuan Anh Hoang
Dissertations and Theses Collection (Open Access)
This dissertation addresses the modeling of factors concerning microblogging users' content and behavior. We focus on two sets of factors. The first set includes behavioral factors of users and content items driving content propagation in microblogging. The second set consists of latent topics and communities of users as the users are engaged in content generation and behavior adoptions. These two sets of factors are extremely important in many applications, e.g., network monitoring and recommender systems. In the first part of this dissertation, we identify user virality, user susceptibility, and content virality as three behavioral factors that affect users' behaviors in …
Event Identification And Analysis On Twitter, Qiming Diao
Event Identification And Analysis On Twitter, Qiming Diao
Dissertations and Theses Collection (Open Access)
With the rapid growth of social media, Twitter has become one of the most widely adopted platforms for people to post short and instant messages. Because of such wide adoption of Twitter, events like breaking news and release of popular videos can easily capture people’s attention and spread rapidly on Twitter. Therefore, the popularity and importance of an event can be approximately gauged by the volume of tweets covering the event. Moreover, the relevant tweets also reflect the public’s opinions and reactions to events. It is therefore very important to identify and analyze the events on Twitter. In this dissertation, …
Data Preparation For Social Network Mining And Analysis, Yazhe Wang
Data Preparation For Social Network Mining And Analysis, Yazhe Wang
Dissertations and Theses Collection (Open Access)
This dissertation studies the problem of preparing good-quality social network data for data analysis and mining. Modern online social networks such as Twitter, Facebook, and LinkedIn have rapidly grown in popularity. The consequent availability of a wealth of social network data provides an unprecedented opportunity for data analysis and mining researchers to determine useful and actionable information in a wide variety of fields such as social sciences, marketing, management, and security. However, raw social network data are vast, noisy, distributed, and sensitive in nature, which challenge data mining and analysis tasks in storage, efficiency, accuracy, etc. Many mining algorithms cannot …
Opinion Mining Of Sociopolitical Comments From Social Media, Swapna Gottipati
Opinion Mining Of Sociopolitical Comments From Social Media, Swapna Gottipati
Dissertations and Theses Collection (Open Access)
Opinions are central to almost all human activities by influencing greatly the decision making process. In this thesis, we present the problems of mining issues, extracting entities and suggestive opinions towards the entities, detecting thoughtful comments, and extracting stances and ideological expressions from online comments in the sociopolitical domain. This study is essential for opinion mining applications that are beneficial for policy makers, government sectors and social organizations. Much work has been done to try to uncover consumer sentiments from online comments to help businesses improve their products and services. However, sociopolitical opinion mining poses new challenges due to complex …
On Predicting User Affiliations Using Social Features In Online Social Networks, Minh Thap Nguyen
On Predicting User Affiliations Using Social Features In Online Social Networks, Minh Thap Nguyen
Dissertations and Theses Collection (Open Access)
User profiling such as user affiliation prediction in online social network is a challenging task, with many important applications in targeted marketing and personalized recommendation. The research task here is to predict some user affiliation attributes that suggest user participation in different social groups.
Social Correlation In Latent Spaces For Complex Networks, Freddy Chong Tat Chua
Social Correlation In Latent Spaces For Complex Networks, Freddy Chong Tat Chua
Dissertations and Theses Collection (Open Access)
This dissertation addresses the subject of measuring social correlation among users within a complex social network. Social correlation is closely related to the measurement of social influence in social sciences. While social influence focuses on the existence of causal influence among users, we take a computational approach to measure correlation strength among users based on their shared interactions. We call this social correlation. To formally model social correlation, we propose a framework which contains two major parts. The first part is that of representing users behavior in a computationally efficient and accurate manner. For example, social media users perform many …
Anomaly Detection On Social Data, Hanbo Dai
Anomaly Detection On Social Data, Hanbo Dai
Dissertations and Theses Collection (Open Access)
The advent of online social media including Facebook, Twitter, Flickr and Youtube has drawn massive attention in recent years. These online platforms generate massive data capturing the behavior of multiple types of human actors as they interact with one another and with resources such as pictures, books and videos. Unfortunately, the openness of these platforms often leaves them highly susceptible to abuse by suspicious entities such as spammers. It therefore becomes increasingly important to automatically identify these suspicious entities and eliminate their threats. We call these suspicious entities anomalies in social data, as they often hold different agenda comparing to …
Fair Cost Sharing Auction Mechanisms In Last Mile Ridesharing, Duc Thien Nguyen
Fair Cost Sharing Auction Mechanisms In Last Mile Ridesharing, Duc Thien Nguyen
Dissertations and Theses Collection (Open Access)
With rapid growth of transportation demands in urban cities, one major challenge is to provide efficient and effective door-to-door service to passengers using the public transportation system. This is commonly known as the Last Mile problem. In this thesis, we consider a dynamic and demand responsive mechanism for Ridesharing on a non-dedicated commercial fleet (such as taxis). This problem is addressed as two sub-problems, the first of which is a special type of vehicle routing problems (VRP). The second sub-problem, which is more challenging, is to allocate the cost (i.e. total fare) fairly among passengers. We propose auction mechanisms where …
Impact Of Multimedia In Sina Weibo, Xun Zhao
Impact Of Multimedia In Sina Weibo, Xun Zhao
Dissertations and Theses Collection (Open Access)
Multimedia contents such as images and videos are widely used in social network sites nowadays. Sina Weibo, a Chinese microblogging service, is one of the first microblog platforms to incorporate multimedia content sharing features. This thesis provides statistical analysis on how multimedia contents are produced, consumed, and propagated in Sina Weibo. Based on 230 million tweets and 1.8 million user profiles in Sina Weibo, we study the impact of multimedia contents on the popularity of both users and tweets as well as tweet life span. In addition to consider the multimedia impact on popularity, we also compare the user influence …
Predictive Modeling For Navigating Social Media, Meiqun Hu
Predictive Modeling For Navigating Social Media, Meiqun Hu
Dissertations and Theses Collection (Open Access)
Social media changes the way people use the Web. It has transformed ordinary Web users from information consumers to content contributors. One popular form of content contribution is social tagging, in which users assign tags to Web resources. By the collective efforts of the social tagging community, a new information space has been created for information navigation. Navigation allows serendipitous discovery of information by examining the information objects linked to one another in the social tagging space. In this dissertation, we study prediction tasks that facilitate navigation in social tagging systems. For social tagging systems to meet complex navigation needs …