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With the boom of social media, the real-world topics are often discussed on the Web via microblogs, which forms oceans of short texts hidden various topics. These topics in microblogs often contain different content and different emotion. How to automatically discover these topics from the high volume of microblogs is a significant question. Although traditional topic discovery methods can discover...
This paper considers detection and error control coding for the 2-D magnetic recording (TDMR) channel modeled with the 2-D four-rectangular-grain model (FRGM). This simple model captures the effects of different 2-D grain sizes and shapes, as well as the TDMR grain overwrite effect. We construct a row-by-row Bahl-Cocke-Jelinek-Raviv-based detector that processes two rows at a time. Simulation results...
As a new kind of social media, query log gains mass size of users and data. It's easy for people to post on query log. Also, the posts spread fast and can be easily seen by many other users. For the reasons above, users post various and large number contents on query log. Among these posts, we find numerous posts that express authors purchase wish for a certain product, in other words, consumption...
The rating (score) and knowledge of the payment behavior of a client to reduce the time of granting of consumer credit is one of the requirements that financial institutions have dedicated to providing these services. For qualifying customers, these entities are based on qualitative and quantitative information of a client, making it difficult a homogeneous rating. Because of the need to reduce response...
Social media crises pose significant challenges for organizations in terms of their rapid rate of spread and potential persistent negative associations in terms of brand parameters and sustained negative advocacy by internet users and/or consumers. This paper reports on a technique for detecting social media crises using social set analysis-an approach to computational social based on associational...
We carefully revisit our definition of a social media signal from previous work both in terms of time-varying features within the data and the networked nature of the medium. Further, we detail our analysis of global patterns in Twitter over the month of June 2014, detect and categorize events, and illustrate how these analyses can be used to inform graph-based models of Twitter, namely using a recent...
Revealing underlying social influence among users in social media is critical to understanding how users interact, on which a lot of security intelligence applications can be built. Existing methods fail to take into account the interaction relationships among memes. In this paper, we propose to simultaneously model social influence and meme interaction in information diffusion with novel multidimensional...
The current Analytics tools and models that are available in the market are very costly, unable to handle Big Data and less secure. The traditional Analytics systems takes a long time to come up with results, so it is not beneficial to use for Real Time Analytics. So, the proposed work resolves all these problems by combining the Apache Open Source platform which solves the issues of Real Time Analytics...
This paper investigates the constituents of Big Data and their contribution to its success. The starting point is the mainstream understanding of Big Data, which defines the volume, variety and velocity (3V) of the underlying data as main properties of the Big Data phenomenon. This definition is challenged through the presented analysis of more than 100 success stories which are offered by vendors...
The crowd funding phenomenon has garnered a considerable amount of attention in recent years. Several online crowd funding platforms have risen to prominence, they can be characterized as two-sided marketplaces. Recent research reveals initial insights into the dynamics and characteristics of crowd funding networks arising from such marketplaces. This research, though, is restricted primarily to analyses...
Crisis informatics investigates how society's pervasive access to technology is transforming how it responds to mass emergency events. To study this transformation, researchers require access to large sets of data that because of their volume and heterogeneous nature are difficult to collect and analyze. To address this concern, we have designed and implemented an environment -- EPIC Analyze -- that...
This paper concerns multi-agent models predicting Twitter trends. We use a step-wise approach to develop a novel agent-based model with the following properties: (1) it uses individual behavior parameters for a set of Twitter users and (2) it uses a retweet graph to model the underlying social network structure of these Twitter users to predict trends. The model parameters can be optimized using empirical...
Detecting and forecasting civil unrest events (protests, strikes, etc.) is of key interest to social scientists and policy makers because these events can lead to significant societal and cultural changes. We analyze protest dynamics in six countries of Latin America on a daily level, from November 2012 through August 2014, using multiple data sources that capture social, political and economic contexts...
Cyber bullying is a new phenomenon resulting from the advance of new communication technologies including the Internet, cell phones and Personal Digital Assistants. It is a challenging bullying problem occurring in a new territory. Online bullying can be particularly damaging and upsetting because it's usually anonymous or hard to trace. In this paper, the proposed method is utilizing a dataset of...
Threaded debate forums have become one of the major social media platforms. Usually people argue with one another using not only claims and evidences about the topic under discussion but also language used to organize them, which we refer to as shell. In this paper, we study how to separate shell from topical contents using unsupervised methods. Along this line, we develop a latent variable model...
Given massive heterogeneous online media, how can we summarize events, and discover causal relationships among them, in real time? Indeed we are living in a deluge of information, everyday hundreds of thousands of news articles are published, millions of postings from social media and internet forums are written, and billions of search queries are generated by Internet users. To convey user-interested...
Social media is a popular platform for spammers to unfairly overwhelm normal users with unwanted or fake content via social networking. The spammers significantly hinder the use of social media systems for effective information dissemination and sharing. Different from the spammers in traditional platforms such as email and the Web, spammers in social media can easily connect with each other, sometimes...
Online communications not only provide instantaneous and inexpensive mean for socialization, but also present an opportunity to understand human relationship. In this paper, we investigated correlation between human social relationship and online communications and modelled personal and business affinity as a linear combination of online interactions. We discovered that personal and business affinities...
As one of aimed items at Smart Television (Smart TV) and Internet Protocol Television (IPTV), it has been stressed to share watching and enjoying the programs among audiences by using social networks. There have been several proposals to use various approaches. However, the progress of standardization efforts, especially to define an appropriate reputational Ontology for improving the quality of IPTV...
Web social media has become one of the major channels for people to express their opinions, share their feelings and communicate with others. Public opinions often ebb and flow with time due to the occurrence of social events and mutual influence of people on certain topics. The dynamic change of public opinions reflects the evolvement and trend of public attitudes and can facilitate many security-related...
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