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A content analysis of online sex worker advertisements suggests specific terms, sources and patterns of behavior that may help identify potential sex trafficked victims within these virtual environments. While some ads are posted by independent sex workers, others may have been posted by traffickers or pimps, advertising the women they have under their control. A total of 600 ads from the Backpage...
Companies today are developing business strategies taking into consideration behavior of their customers through social networks, which have allowed to extract large amounts of relevant data about users. This is why it has been necessary to apply data mining techniques to find patterns that describe the preferences of users in different contexts. This paper describes the results of using data mining...
Many recent studies on finance and social networks discovered that investor's attention is correlated to the financial market movement in terms of the price shocks. Following related findings, a significant and challenging problem is to forecast the direction of the market movement based on vast social media activities. Appropriately processing social networks data and developing models to capture...
To incentivize users' participations, online social networks often provide users with various rewards for their contributions to the sites. Attracted by the rewards, users will spend more time using the network services. Specifically, in this paper, we will mainly focus on “badges reward systems”. Badges are small icons attached to users' homepages and profiles denoting their achievements. People...
Efficient organization and analysis of academic information has many advantages. Most scholar retrieval systems appeared these years can perform keyword-based paper search. However, performing large-scale expert and paper retrieval is an intractable problem. Here we present a platform that can not only reduce the workload of researchers when searching academic literature, but also promote academic...
We study a natural problem: Given a small piece of a large parent network, is it possible to identify the parent network? We approach this problem from two perspectives. First, using several “sophisticated” or “classical” network features that have been developed over decades of social network study. These features measure aggregate properties of the network and have been found to take on distinctive...
In community question and answering sites, pairs of questions and their high-quality answers (like best answers selected by askers) can be valuable knowledge available to others. However lots of questions receive multiple answers but askers do not label either one as the accepted or best one even when some replies answer their questions. To solve this problem, high-quality answer prediction or best...
This paper introduces two models for influence in networks, and presents some upper and lower bounds for time needed to reach stability in these models. The first, called the Majority Model, is an expansion on the “Democrats and Republicans Model” that uses cascades to initialize the influence network rather than randomly assigning each node an initial opinion. By slightly modifying a network introduced...
This paper discusses part one of the main work in field of data science, mining and analytics. Family of algorithms is developed to predict the educational relevance of individuals' talents through lens of personality features (unstructured and semi-structured) and academic/career data. The big data (unstructured and semi-structured) contains lots of valuable information that can be mined and analyzed...
We study the problem of synopsis construction of massive graph streams arriving in real-time. Many graphs such as those formed by the activity on social networks, communication networks, and telephone networks are defined dynamically as rapid edge streams on a massive domain of nodes. In these rapid and massive graph streams, it is often not possible to estimate the frequency of individual items (e...
Nowadays, in the world of limited attention, the techniques that maximize the spread of social influence are more than welcomed. Companies try to maximize their profits on sales by providing customers with free samples believing in the power of word-of-mouth marketing, governments and non-governmental organizations often want to introduce positive changes in the society by appropriately selecting...
Skyline queries are currently the most notable type of multi-criteria search algorithm. A skyline query returns all of the data points in a given a dataset that are not dominated by other data points. However, this type of query is limited by the fact that the number of results cannot be controlled. In some cases, this can result in an excessive number of results, whereas other cases result in an...
We have built a tool for inspecting and managing data lakes. The motivations for creating this tool are 1) schema discovery (determining links pertinent to solving a data analysis problem), 2) discovering high risk links in data schemas that give rise to Information Security problems and 3) discovering high value relationships enabling data asset curation. The tool works by extracting metadata from...
Networks extracted from social media platforms frequently include multiple types of links that dynamically change over time; these links can be used to represent dyadic interactions such as economic transactions, communications, and shared activities. Organizing this data into a dynamic multiplex network, where each layer is composed of a single edge type linking the same underlying vertices, can...
Being the anchor points for building social relationships in the cyberspace, online social networks (OSNs) play an integral part of modern peoples life. Since different OSNs are designed to address specific social needs, people take part in multiple OSNs to cover different facets of their life. While the fragmented pieces of information about a user in each OSN may be of limited use, serious privacy...
Traditional network classification techniques will become computationally intractable when applied on a network which is presented in a streaming fashion with continuous updates. In this paper, we examine the problem of classification in dynamic streaming networks, or graphs. Two scenarios have been considered: the graph transaction scenario and the one large graph scenario. We propose a unified framework...
Although OSNs are major and growing large scale web applications, there is still a lack of workload models and tools for performance evaluation and testability studies. This fact motivates us to develop a general purpose benchmark for evaluating the main hardware and software resources associated to this kind of applications. To this end, we have developed a flexible workload model based on interactive...
We focus on analysis of dominance, power, influence — that by definition asymmetric — between pairs of individuals in social networks. We conduct dominance analysis based on the canonical analysis of asymmetry that decomposes a square asymmetric matrix into two parts, a symmetric one and a skew-symmetric one, and then applies the singular value decomposition (SVD) on the skew-symmetric part. Each...
People usually get involved in multiple social networks to enjoy new services or to fulfill their needs. Many new social networks try to attract users of other existing networks to increase the number of their users. Once a user (called source user) of a social network (called source network) joins a new social network (called target network), a new inter-network link (called anchor link) is formed...
We present a new method for detecting descriptive community patterns capturing exceptional (sequential) link trails. For that, we provide a novel problem formalization: We model sequential data as first-order Markov chain models, mapped to an attributed weighted network represented as a graph. Then, we detect subgraphs (communities) using exceptional model mining techniques: We target subsets of sequential...
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