Physical Sciences and Mathematics Commons^™

Anomaly Detection Through Enhanced Sentiment Analysis On Social Media Data, Zhaoxia Wang, Victor Joo, Chuan Tong, Xin Xin, Hoong Chor Chin

Research Collection School Of Computing and Information Systems

Anomaly detection in sentiment analysis refers to detecting abnormal opinions, sentiment patterns or special temporal aspects of such patterns in a collection of data. The anomalies detected may be due to sudden sentiment changes hidden in large amounts of text. If these anomalies are undetected or poorly managed, the consequences may be severe, e.g. A business whose customers reveal negative sentiments and will no longer support the establishment. Social media platforms, such as Twitter, provide a vast source of information, which includes user feedback, opinion and information on most issues. Many organizations also leverage social media platforms to publish information …

Issues Of Social Data Analytics With A New Method For Sentiment Analysis Of Social Media Data, Zhaoxia Wang, Victor J. C. Tong, David Chan

Research Collection School of Social Sciences

Social media data consists of feedback, critiques and other comments that are posted online by internet users. Collectively, these comments may reflect sentiments that are sometimes not captured in traditional data collection methods such as administering a survey questionnaire. Thus, social media data offers a rich source of information, which can be adequately analyzed and understood. In this paper, we survey the extant research literature on sentiment analysis and discuss various limitations of the existing analytical methods. A major limitation in the large majority of existing research is the exclusive focus on social media data in the English language. There …

On Joint Modeling Of Topical Communities And Personal Interest In Microblogs, Tuan-Anh Hoang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In this paper, we propose the Topical Communities and Personal Interest (TCPI) model for simultaneously modeling topics, topical communities, and users’ topical interests in microblogging data. TCPI considers different topical communities while differentiating users’ personal topical interests from those of topical communities, and learning the dependence of each user on the affiliated communities to generate content. This makes TCPI different from existing models that either do not consider the existence of multiple topical communities, or do not differentiate between personal and community’s topical interests. Our experiments on two Twitter datasets show that TCPI can effectively mine the representative topics for …

Improving The Efficacy Of Web-Based Educational Outreach In Ecology, Gregory R. Goldsmith, Andrew D. Fulton, Colin D. Witherill, Javier F. Espeleta

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Scientists are increasingly engaging the web to provide formal and informal science education opportunities. Despite the prolific growth of web-based resources, systematic evaluation and assessment of their efficacy remains limited. We used clickstream analytics, a widely available method for tracking website visitors and their behavior, to evaluate 60,000 visits over three years to an educational website focused on ecology. Visits originating from search engine queries were a small proportion of the traffic, suggesting the need to actively promote websites to drive visitation. However, the number of visits referred to the website per social media post varied depending on the social …

Information Security Newsletter

Information Security Newsletter

No abstract provided.

Partisan Sharing: Facebook Evidence And Societal Consequences, Jisun An, Daniele Quercia, Jon Crowcroft

Research Collection School Of Computing and Information Systems

The hypothesis of selective exposure assumes that people seek out information that supports their views and eschew information that conflicts with their beliefs, and that has negative consequences on our society. Few researchers have recently found counter evidence of selective exposure in social media: users are exposed to politically diverse articles. No work has looked at what happens after exposure, particularly how individuals react to such exposure, though. Users might well be exposed to diverse articles but share only the partisan ones. To test this, we study partisan sharing on Facebook: the tendency for users to predominantly share like-minded news …

A Crowdsourcing Approach To Identify Common Method Bias And Self-Representation, Margeret A. Hall, Simon Caton

Interdisciplinary Informatics Faculty Proceedings & Presentations

Pertinent questions on the measurement of social indicators are: the verification of data gained online (e.g., controlling for self-representation on social networks), and appropriate uses in community management and policy-making. Across platforms like Facebook, LinkedIn, Twitter, and blogging services, users (sub)consciously represent themselves in a way which is appropriate for their intended audience (Qui et al., 2012; Zhao et al., 2008). However, scholars in the social sciences and computer science have not yet adequately addressed controlling for self-representation, or the propensity to display or censor oneself, in their analyses (Zhao et al., 2008; Das and Kramer, 2013). As such researchers …

Sharing Political News: The Balancing Act Of Intimacy And Socialization In Selective Exposure, Jisun An, Daniele Quercia, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft

Research Collection School Of Computing and Information Systems

One might think that, compared to traditional media, social media sites allow people to choose more freely what to read and what to share, especially for politically oriented news. However, reading and sharing habits originate from deeply ingrained behaviors that might be hard to change. To test the extent to which this is true, we propose a Political News Sharing (PoNS) model that holistically captures four key aspects of social psychology: gratification, selective exposure, socialization, and trust & intimacy. Using real instances of political news sharing in Twitter, we study the predictive power of these features. As one might expect, …

Non-Learning Semantic Analysis For Context Discovery And Sentiment Estimation: Transportation Application, Himanshu Verma

UNLV Theses, Dissertations, Professional Papers, and Capstones

With enormous amount of linguistic data present on web, text analysis has become one of the major fields of interest today. This field includes sentiment analysis, information retrieval, text document classification, knowledge based modeling, content similarity measure, data clustering, words prediction/correction, decision making etc. Managing and processing such data has vital importance. The field being quite broad, our focus is mainly on transportation related social media(Twitter) data extraction, text categorization/classification which can be further sub-divided into concept discovery, word sense disambiguation and sentiment analysis to analyze performance of existing transportation system worldwide. Concept discovery is the method of extracting the …

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 …

Lexicon-Based Sentiment Analysis In The Social Web, Fazal Masud Kundi, Dr. Muhammad Zubair Asghar

Dr. Muhammad Zubair Asghar

Sentiment analysis is a compelling issue for both information producers and consumers. We are living in the “age of customer”, where customer knowledge and perception is a key for running successful business. The goal of sentiment analysis is to recognize and express emotions digitally. This paper presents the lexicon-based framework for sentiment classification, which classifies tweets as a positive, negative, or neutral. The proposed framework also detects and scores the slangs used in the tweets. The comparative results show that the proposed system outperforms the existing systems. It achieves 92% accuracy in binary classification and 87% in multi-class classification.

Bits Of Research, Michele C. Weigle

Computer Science Presentations

PDF of a powerpoint presentation that provides an overview of digital preservation, web archiving, and information visualization research; dated June 26, 2014. Also available on Slideshare.

The Lived Experience Of Young Adult Burn Survivors' Use Of Social Media, Marie S. Giordano

Dissertations, Theses, and Capstone Projects

The purpose of this phenomenological study was to illuminate the meaning of social media use by young adult burn survivors. Five females and four males, aged 20-25, who sustained burns > 25%, were interviewed. Van Manen's (1999) phenomenological methodology provided the framework for this study. The meaning of the context of the lived experience is described in the five essential themes of identity, connectivity, social support, making meaning, and privacy. These young adult burn survivors, having experienced the traumatic effects of a burn during adolescence, use social media as a way of expressing their identity, while being cautious about privacy. Part …

Aidr: Artificial Intelligence For Disaster Response, Muhammad Imran, Carlos Castillo, Ji Lucas, Patrick Meier, Sarah Vieweg

Muhammad Imran

We present AIDR (Artificial Intelligence for Disaster Response), a platform designed to perform automatic classification of crisis-related microblog communications. AIDR enables humans and machines to work together to apply human intelligence to large-scale data at high speed. The objective of AIDR is to classify messages that people post during disasters into a set of user-defined categories of information (e.g., "needs", "damage", etc.) For this purpose, the system continuously ingests data from Twitter, processes it (i.e., using machine learning classification techniques) and leverages human-participation (through crowdsourcing) in real-time. AIDR has been successfully tested to classify informative vs. non-informative tweets posted during …

Inferences & Connections, Tamara Kneese

Media Studies

Data-oriented systems are inferring relationships between people based on genetic material, behavioral patterns (e.g., shared geography imputed by phone carriers), and performed associations (e.g., "friends" online or shared photographs). What responsibilities do entities who collect data that imputes connections have to those who are implicated by association? For example, as DNA and other biological materials are collected outside of medicine (e.g., at point of arrest, by informatics services like 23andme, for scientific inquiry), what rights do relatives (living, dead, and not-yet-born) have? In what contexts is it acceptable to act based on inferred associations and in which contexts is it …

The Influence And Deception Of Twitter: The Authenticity Of The Narrative And Slacktivism In The Australian Electoral Process, Benjamin Waugh, Maldini Abdipanah, Omid Hashemi, Shaquille A. Rahman, David M. Cook

Dr. David M Cook

It is uncertain how many discreet users occupy the social media community. Fake tweets, sock puppets, force‐multipliers and botnets have become embedded within the fabric of new media in sufficient numbers that social media support by means of quantity is no longer a reliable metric for determining authority and influence within openly expressed issues and causes. Election campaigns, and their associated political agendas, can now be influenced by non‐specific virtual presences that cajole and redirect opinions without declaring identity or allegiance. In the lead up to the 2013 Australian Federal Election, the open source Twitter activity for the two major …

The Bad Guys Are Using It, Are You?, Hong-Eng Koh

Australian Security and Intelligence Conference

From Occupy Wall Street to 2011 England riots to Arab Spring to Mumbai 26/11 to the ethnic cleansing rumors in India and increasingly used by pedophiles, social media is a very powerful tool for pedophiles, troublemakers, criminals and even terrorists to target individuals and even to go against the establishment. On the other hand, social media can save lives in a disaster, and its a natural extension of community policing or engagement. Community engagement is a must-have strategy for any public safety and security agency. However, this strategy requires the removal of stovepipe processes and systems within an agency, allowing …

[Introduction To] Identity And Leadership In Virtual Communities: Establishing Credibility And Influence, Dona J. Hickey, Joe Essid

Bookshelf

The presence and ubiquity of the internet continues to transform the way in which we identify ourselves and others both online and offline. The development of virtual communities permits users to create an online identity to interact with and influence one another in ways that vary greatly from face-to-face interaction.

Identity and Leadership in Virtual Communities: Establishing Credibility and Influence explores the notion of establishing an identity online, managing it like a brand, and using it with particular members of a community. Bringing together a range of voices exemplifying how participants in online communities influence one another, this book serves …

Developing A Conceptual Framework For Modeling Deviant Cyber Flash Mob: A Socio-Computational Approach Leveraging Hypergraph Constructs, Samer Al-Khateeb, Nitin Agarwal

Journal of Digital Forensics, Security and Law

In a Flash Mob (FM) a group of people get together in the physical world perform an unpredicted act and disperse quickly. Cyber Flash Mob (CFM) is the cyber manifestation of flash mob coordinated primarily using social media. Deviant Cyber Flash Mob (or, DCFM) is a special case of CFM, which is categorized as the new face of transnational crime organizations (TCOs). The DCFM phenomenon can be considered as a form of a cyber-collective action that is defined as an action aiming to improve group’s conditions (such as, status or power). In this paper, we conduct a conceptual analysis of …

Locational Wireless And Social Media-Based Surveillance, Maxim Chernyshev

Australian Digital Forensics Conference

The number of smartphones and tablets as well as the volume of traffic generated by these devices has been growing constantly over the past decade and this growth is predicted to continue at an increasing rate over the next five years. Numerous native features built into contemporary smart devices enable highly accurate digital fingerprinting techniques. Furthermore, software developers have been taking advantage of locational capabilities of these devices by building applications and social media services that enable convenient sharing of information tied to geographical locations. Mass online sharing resulted in a large volume of locational and personal data being publicly …

Public Social Network Sites And Social Recruiting, Abby Peters

Open Access Theses & Dissertations

Social network sites (SNSs) are an increasingly popular form of social media used by individuals and organizations. As these platforms continue to transform the way people communicate with one another, they are simultaneously revolutionizing the way individuals interact with organizations. Part of this dramatic change is apparent in the processes by which organizations are recruiting employees and job seekers are pursuing employment. To investigate these phenomena, I employed the diffusion of innovations theory in a SNS context to examine the relationship between organizations' use of their corporate career website and their use of SNSs as recruiting sources. Subsequently, I used …