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Following the trend of privacy preserving online social network publishing, various anonymization mechanisms have been designed and employed. Many differential privacybased mechanisms claim that they can preserve the utility as well as guarantee the privacy. Their utility analysis are always based on some specifically chosen metrics.This paper aims to find a novel angle that describing the network...
The amount of data circulating on the Internet is increasing day by day. With the increasing use of social media in particular, the importance of analyzing these data is increasing. The use of machine learning approaches to analyze large amounts of data is still popular today. Today, the social network Facebook is the most popular social networking sites. In this study, some data taken on Facebook...
Online Social Networks (OSNs) are simple, unweighted graphs used to store information in the context of social media and emails. Accurately representing the connectivity and features of these graphs is important in applications of graph utility and differential privacy. Current methods of describing these network graphs use graph metrics such as the shortest-path betweenness centrality, clustering...
Getting the daily news from social media has nowadays become a common practice among people. Unreliable sources of information expose people to a dose of hoaxes, rumours, conspiracy theories and misleading news. Mixing both reliable and unreliable information on social media has made the truth to be hardly determined. Academic research indicates an increasing reliance of online users on social media...
Over the years social network data has been mined to predict individuals' traits such as intelligence and sexual orientation. While mining social network data can provide many beneficial services to the user such as personalized experiences, it can also harm the user when used in making critical decisions such as employment. In this work, we investigate the reliability of applying data mining techniques...
In this study we performed an initial investigation and evaluation of altmetrics and their relationship with public policy citation of research papers. We examined methods for using altmetrics and other data to predict whether a research paper is cited in public policy and applied receiver operating characteristic curve on various feature groups in order to evaluate their potential usefulness. From...
Memcached is a widely used in-memory caching solution in large-scale searching scenarios. The most pivotal performance metric in Memcached is latency, which is affected by various factors including the workload pattern, the service rate, the unbalanced load distribution and the cache miss ratio. To quantitate the impact of each factor on latency, we establish a theoretical model for the Memcached...
Political parties have not been indifferent to the opportunities offered by the internet-based technologies. Today, political parties use the social media tools to communicate, organize and mobilize. However, few studies focus on the use of social media by the political parties and these studies analyze the use of social media in election campaigns. Therefore, in the relevant literature, there is...
Popularity in social media is an important objective for professional users (e.g. companies, celebrities, and public figures, etc). A simple yet prominent metric utilized to measure the popularity of a user is the number of fans or followers she succeed to attract to her page. Popularity is influenced by several factors which identifying them is an interesting research topic. This paper aims to understand...
Gephi is an open source tool, used for Data Analysis, Link Analysis, Social Network Analysis, Biological Network Analysis, Poster Creation. Gephi tool in this project is used for Social Network Analysis of Facebook Pages and is used to find metrics like Modularity, Average Weighted Degree, Average Degree etc. The Gephi tool gives different graphs as output which can be analyzed by the shape of the...
Software development remains a predominantly male activity, despite coordinated efforts from research, industry, and policy makers. This gender imbalance is most visible in social programming, on platforms such as Stack Overflow.To better understand the reasons behind this disparity, and off er support for (corrective) decision making, we and others have been engaged in large-scale empirical studies...
With the increasing use of digital technologies, online social networks are emerging as major means of communication. Recently, social networks such as Facebook and Twitter are also being used by consumers, care providers (physicians, hospitals), and government agencies to share health related information. The asymmetric user network and the short message size have made Twitter particularly popular...
With the exponential rise in the number of Internet users, Social Networking platforms have become one of the major means of communication all over the globe. Many major players in this field exist including the likes of Facebook, Twitter, Google+ etc. Impressed by the number of users an individual can reach using the existing Social Networking platforms, most organizations and celebrities make use...
In this paper, we motivate the utility of framing very common data analysis and business intelligence problems as a problem in understanding the differences between two datasets. We call this framework the Difference-of-Datasets (DoD) framework. We propose a simple and effective method to help find the root causes of changes, i.e. “Why did the observed change happen?” or “What drove the observed change?”...
In this paper, we report our primary findings in detecting spam profiles on Facebook social media. As we already know, spam profiles on social media especially Facebook is often used as a place to spread spam. Spammers generally use wall post feature on Facebook to spread spam. In addition spammers are also targeting page on Facebook which is a community of many people. In this community, spammers...
Motivated by Online Ad allocation with advertisers that pursue multiple objectives, we introduce and study a problem of Ad Allocation with Secondary Metrics. For instance, advertisers pay per click which is the primary metric the platforms optimize for, but require the average cost of a conversion — the secondary metric — to be below some threshold. This is an explicit option for Facebook advertisers...
In the last years a new right-wing, populist and eurosceptic party emerged in Germany, the 'Alternative für Deutschland'. Topics that were used by the party to draw attention to their program included the Euro-crisis and the so-called 'refugee crisis'. We investigate some aspects of social media use of the AfD. Our goal is to relate the rise of this party to some quantitative measures of their social...
Web 2.0 technologies have brought new ways of connecting people in social networks for collaboration and communication in various on-line communities. Social network analysis (SNA) is used to model social relationships as nodes (individuals, organizations: actors) and edges (relationships between these nodes). This analysis is based on a structural approach in order to describe relations between Facebook...
Predicting the future popularity of online content is highly important in many applications. Under preferential attachment influence popular items get more popular thereby resulting in long tailed distribution problem. Consequently, new items which can be popular (potential ones), are suppressed by the already popular items. This paper proposes a novel model which is able to identify potential items...
Along with the explosive growth of mobile social network (MSN) users and the advent of device-to-device (D2D) communications, D2D-based MSN (D2D-MSN) has become a promising alternative for exchanging multimedia contents on-the-go. Although the complete structure of a D2D-MSN plays a key role in understanding its performance, such knowledge is not readily available due to the difficulty of collecting...
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