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Full-Text Articles in Physical Sciences and Mathematics
Inferring Social Media Users’ Demographics From Profile Pictures: A Face++ Analysis On Twitter Users, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Joni Salminen, Bernard J. Jansen
Inferring Social Media Users’ Demographics From Profile Pictures: A Face++ Analysis On Twitter Users, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Joni Salminen, Bernard J. Jansen
Research Collection School Of Computing and Information Systems
In this research, we evaluate the applicability of using facial recognition of social media account profile pictures to infer the demographic attributes of gender, race, and age of the account owners leveraging a commercial and well-known image service, specifically Face++. Our goal is to determine the feasibility of this approach for actual system implementation. Using a dataset of approximately 10,000 Twitter profile pictures, we use Face++ to classify this set of images for gender, race, and age. We determine that about 30% of these profile pictures contain identifiable images of people using the current state-of-the-art automated means. We then employ …
Multilingual Sentiment Analysis : From Formal To Informal And Scarce Resource Languages, Siaw Ling Lo, Erik Cambria, Raymond Chiong, David Cornforth
Multilingual Sentiment Analysis : From Formal To Informal And Scarce Resource Languages, Siaw Ling Lo, Erik Cambria, Raymond Chiong, David Cornforth
Research Collection School Of Computing and Information Systems
The ability to analyse online user-generated content related to sentiments (e.g., thoughts and opinions) on products or policies has become a de-facto skillset for many companies and organisations. Besides the challenge of understanding formal textual content, it is also necessary to take into consideration the informal and mixed linguistic nature of online social media languages, which are often coupled with localised slang as a way to express ‘true’ feelings. Due to the multilingual nature of social media data, analysis based on a single official language may carry the risk of not capturing the overall sentiment of online content. While efforts …
Leveraging Social Analytics Data For Identifying Customer Segments For Online News Media, Jansen, Bernard J, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Haewoon Kwak
Leveraging Social Analytics Data For Identifying Customer Segments For Online News Media, Jansen, Bernard J, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Haewoon Kwak
Research Collection School Of Computing and Information Systems
In this work, we describe a methodology for leveraging large amounts of customer interaction data with online content from major social media platforms in order to isolate meaningful customer segments. The methodology is robust in that it can rapidly identify diverse customer segments using solely online behaviors and then associate these behavioral customer segments with the related distinct demographic segments, presenting a holistic picture of the customer base of an organization. We validate our methodology via the implementation of a working system that rapidly and in near real-time processes tens of millions of online customer interactions with content posted on …
A Framework For Recommendation Of Highly Popular News Lacking Social Feedback, Nuno Moniz, Luís Torgo, Magdalini Eirinaki, Paula Branco
A Framework For Recommendation Of Highly Popular News Lacking Social Feedback, Nuno Moniz, Luís Torgo, Magdalini Eirinaki, Paula Branco
Faculty Publications
Social media is rapidly becoming the main source of news consumption for users, raising significant challenges to news aggregation and recommendation tasks. One of these challenges concerns the recommendation of very recent news. To tackle this problem, approaches to the prediction of news popularity have been proposed. In this paper, we study the task of predicting news popularity upon their publication, when social feedback is unavailable or scarce, and to use such predictions to produce news rankings. Unlike previous work, we focus on accurately predicting highly popular news. Such cases are rare, causing known issues for standard prediction models and …
Am I Who I Say I Am? Unobtrusive Selfrepresentation And Personality Recognition On Facebook, Margeret A. Hall, Simon Caton
Am I Who I Say I Am? Unobtrusive Selfrepresentation And Personality Recognition On Facebook, Margeret A. Hall, Simon Caton
Interdisciplinary Informatics Faculty Publications
Across social media platforms users (sub)consciously represent themselves in a way which is appropriate for their intended audience. This has unknown impacts on studies with unobtrusive designs based on digital (social) platforms, and studies of contemporary social phenomena in online settings. A lack of appropriate methods to identify, control for, and mitigate the effects of self-representation, the propensity to express socially responding characteristics or self-censorship in digital settings, hinders the ability of researchers to confidently interpret and generalize their findings. This article proposes applying boosted regression modelling to fill this research gap. A case study of paid Amazon Mechanical Turk …
Web-Based Interactive Social Media Visual Analytics, Diego Rodríguez-Baquero, Jiawei Zhang, David S. Ebert, Sorin A. Matei
Web-Based Interactive Social Media Visual Analytics, Diego Rodríguez-Baquero, Jiawei Zhang, David S. Ebert, Sorin A. Matei
The Summer Undergraduate Research Fellowship (SURF) Symposium
Real-time social media platforms enable quick information broadcasting and response during disasters and emergencies. Analyzing the massive amount of generated data to understand the human behavior requires data collection and acquisition, parsing, filtering, augmentation, processing, and representation. Visual analytics approaches allow decision makers to observe trends and abnormalities, correlate them with other variables and gain invaluable insight into these situations. In this paper, we propose a set of visual analytic tools for analyzing and understanding real-time social media data in times of crisis and emergency situations. First, we model the degree of risk of individuals’ movement based on evacuation zones …
Marketing Strategy Of School Of Professional Studies In China, Jiahui Liu, Jing Wang, Shuo An, Wengxing Wang, Yiwei Wang
Marketing Strategy Of School Of Professional Studies In China, Jiahui Liu, Jing Wang, Shuo An, Wengxing Wang, Yiwei Wang
School of Professional Studies
Chinese students are the most visible international presence at many universities across the United States, and the number continues to grow. Since 2010, The number of graduate students studying abroad has entered the period in which the increase has been declining. Under the circumstance of the weak global economy and high cost of education, the administration needs to attract the attention of Chinese students. In the process of competing for applicants, how to develop marketing strategies to attract students’ eyeballs has become an important means of trying to increase school income through Chinese students. The marketing strategy mentioned in this …
Detecting User Demographics In Twitter To Inform Health Trends In Social Media, Christopher R. Markson
Detecting User Demographics In Twitter To Inform Health Trends In Social Media, Christopher R. Markson
Dissertations
The widespread and popular use of social media and social networking applications offer a promising opportunity for gaining knowledge and insights regarding population health conditions thanks to the diversity and abundance of online user-generated information (UGHI) relating to healthcare and well-being. However, users on social media and social networking sites often do not supply their complete demographic information, which greatly undermines the value of the aforementioned information for health 2.0 research, e.g., for discerning disparities across population groups in certain health conditions. To recover the missing user demographic information, existing methods observe a limited scope of user behaviors, such as …
A Domain Based Approach To Social Relation Recognition, Qianru Sun, Bernt Schiele, Mario Fritz
A Domain Based Approach To Social Relation Recognition, Qianru Sun, Bernt Schiele, Mario Fritz
Research Collection School Of Computing and Information Systems
Social relations are the foundation of human daily life. Developing techniques to analyze such relations from visual data bears great potential to build machines that better understand us and are capable of interacting with us at a social level. Previous investigations have remained partial due to the overwhelming diversity and complexity of the topic and consequently have only focused on a handful of social relations. In this paper, we argue that the domain-based theory from social psychology is a great starting point to systematically approach this problem. The theory provides coverage of all aspects of social relations and equally is …
Demographics Of News Sharing In The U.S. Twittersphere, Julio C.S. Reis, Haewoon Kwak, Jisun An, Johnnatan Messias, Benevenuto Fabrıcio.
Demographics Of News Sharing In The U.S. Twittersphere, Julio C.S. Reis, Haewoon Kwak, Jisun An, Johnnatan Messias, Benevenuto Fabrıcio.
Research Collection School Of Computing and Information Systems
The widespread adoption and dissemination of online news through social media systems have been revolutionizing many segments of our society and ultimately our daily lives. In these systems, users can play a central role as they share content to their friends. Despite that, little is known about news spreaders in social media. In this paper, we provide the first of its kind in-depth characterization of news spreaders in social media. In particular, we investigate their demographics, what kind of content they share, and the audience they reach. Among our main findings, we show that males and white users tend to …
Modeling Topics And Behavior Of Microbloggers: An Integrated Approach, Tuan Anh Hoang, Ee-Peng Lim
Modeling Topics And Behavior Of Microbloggers: An Integrated Approach, Tuan Anh Hoang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Microblogging encompasses both user-generated content and behavior. When modeling microblogging data, one has to consider personal and background topics, as well as how these topics generate the observed content and behavior. In this article, we propose the Generalized Behavior-Topic (GBT) model for simultaneously modeling background topics and users' topical interest in microblogging data. GBT considers multiple topical communities (or realms) with different background topical interests while learning the personal topics of each user and the user's dependence on realms to generate both content and behavior. This differentiates GBT from other previous works that consider either one realm only or content …
Ten Simple Rules For Responsible Big Data Research, Matthew Zook, Solon Barocas, Danah Boyd, Kate Crawford, Emily Keller, Seeta Peña Gangadharan, Alyssa Goodman, Rachelle Hollander, Barbara A. Koenig, Jacob Metcalf, Arvind Narayanan, Alondra Nelson, Frank Pasquale
Ten Simple Rules For Responsible Big Data Research, Matthew Zook, Solon Barocas, Danah Boyd, Kate Crawford, Emily Keller, Seeta Peña Gangadharan, Alyssa Goodman, Rachelle Hollander, Barbara A. Koenig, Jacob Metcalf, Arvind Narayanan, Alondra Nelson, Frank Pasquale
Geography Faculty Publications
No abstract provided.
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 …
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 …
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 …
The Creation Of An Arabic Emotion Ontology Based On E-Motive, Anoud Bani-Hani, Munir Majdalweieh, Feras Obeidat
The Creation Of An Arabic Emotion Ontology Based On E-Motive, Anoud Bani-Hani, Munir Majdalweieh, Feras Obeidat
All Works
© 2017 The Authors. Published by Elsevier B.V. There is an increased interest in social media monitoring to analyse massive, free form, short user-generated text from multiple social media sites such as Facebook, WhatsApp and Twitter. Companies are interested in sentiment analysis to understand customers' opinions about their products/services. Governments and law enforcement agencies are interested in identifying threats to safeguard their country's national security. They are actively seeking ways to monitor and analyse the public's responses to various services, activities and events, especially since social media has become a valuable real-time resource of information. This study builds on prior …