We develop in this paper a trend detection algorithm, designed to find trendy topics being disseminated in a social network. We assume that the broadcasts of messages in the social network is governed by a self-exciting point process, namely a Hawkes ...

This paper suggests a voting algorithm for predicting people's choices. Usually, once a new algorithm is offered, one needs to prove the soundness of the algorithm, i.e., showing that the algorithm does the thing it is set up to do. But in the case of ...

In epistemic communities, people are said to be selected on their contribution in knowledge to the project (articles, codes, etc.). However, the socialization process is an important factor for inclusion, sustainability as a contributor, and promotion. ...

In an ever-increasing variety of contexts, people are working collaboratively to solve problems and accomplish tasks. Yet the characteristics of teams that work effectively are not fully understood. We focus on the problem of identifying particularly ...

Various projections or views of a heterogeneous information network can be modeled using the graph OLAP (On-line Analytical Processing) framework for effective decision making. Detecting anomalous projections of the network can help the analysts ...

Today, many people spend a lot of time online. Their social interactions captured in online social networks are an important part of the overall personal social profile, in addition to interactions taking place offline. This paper investigates whether ...

On-line support forums are a common method for businesses to provide product support for customers. In addition to trouble-shooting and how-to guides, on-line forums also serve the important purpose of allowing customers to interact and discuss the ...

Fraud is a social process that occurs over time. We introduce a new approach, called AFRAID, which utilizes active inference to better detect fraud in time-varying social networks. That is, classify nodes as fraudulent vs. non-fraudulent. In active ...

Studying social networks and the ties connecting people in those networks has attracted many researchers. Social networks like Facebook, Twitter and Flickr require efficient and accurate methods to recommend friends to their users in the network. ...

By constructing the social networks of large commercial building managers in a two-phase project, we hope to unveil the catalysts that diffuse energy efficient technologies. Completion of both phases will demonstrate 1) which actors in energy efficiency ...

Personalization of serious games is an important factor for motivating and engaging players. It requires the identification of players' profiles through the analysis of large volume of data including game data. This research study aims at identifying ...

Massive open online course is now a popular choice for online learners. There are many MOOC platforms all over the world. They provide multiple variants of MOOC. Traditionally, students learn by watching videos and doing online quizzes. Course forum is ...

Practitioners and researchers studying Natural Resource Governance (NRG) increasingly pay attention to Social Network Analysis (SNA). Recent research shows that social networks can be an important determinant when conflicting interests deteriorate ...

Community-based question answering (CQA) platforms are crowd-sourced services for sharing user expertise on various topics, from mechanical repairs to parenting. While they naturally build-in an online social network infrastructure, they carry a very ...

Understanding users' sentiments in social media is important in many domains, such as marketing and online applications. Is one demographic group inherently different from another? Does a group express the same sentiment both in private and public? How ...

We show that weak ties offer a useful theoretical lens for understanding the sharing and usage of community-contributed resources amongst educators in a large urban school district. Community-contributed resources include a rich variety of teaching and ...

Traditional classifiers require extracting high dimensional feature representations, which become computationally expensive to process and can misrepresent or deteriorate the accuracy of a classifier. By utilizing a more representative list of extracted ...

We study the problem of trust inference in signed social networks, in which, in addition to rating items, users can also indicate their disposition towards each other through directional signed links. We explore the problem in a semisupervised setting, ...

Who are the best targets to receive a call-for-paper or call-for-participation? What kind of topics should we propose for a workshop or a special issue of next year? Precisely predicting author's topic following behavior, i.e., publishing papers of a ...

In this paper, we study an important issue whether the network properties on mobile social networks are still similar to these on traditional web-based social networks. To explore such answers is important since the paradigm shift has already happened ...