We analyze the information credibility of news propagated through Twitter, a popular microblogging service. Previous research has shown that most messages posted on Twitter are truthful, but service is also used to spread misinformation and false rumors, often unintentionally.

The quality of user-generated content varies drastically from excellent to abuse and spam. As the availability such increases, task identifying high-quality sites based on user contributions --social media -- becomes increasingly important. Social in general exhibit a rich variety information sources: addition itself, there is wide array non-content available, as links between items explicit ratings members community. In this paper we investigate methods for exploiting community feedback...

In this article we explore the behavior of Twitter users under an emergency situation. particular, analyze activity related to 2010 earthquake in Chile and characterize hours days following disaster. Furthermore, perform a preliminary study certain social phenomenons, such as dissemination false rumors confirmed news. We how information propagated through network, with purpose assessing reliability source extreme circumstances. Our analysis shows that propagation tweets correspond differs...

An auxiliary protein which affects the ability of calf thymus DNA polymerase-delta to utilize template/primers containing long stretches single-stranded template has been purified homogeneity from same tissue. The coelutes with on DEAE-cellulose and phenyl-agarose chromatography but is separated polymerase phosphocellulose chromatography. physical functional properties strongly resemble those beta subunit Escherichia coli III holoenzyme. A molecular weight 75,000 calculated a sedimentation...

We present AIDR (Artificial Intelligence for Disaster Response), a platform designed to perform automatic classification of crisis-related microblog communications. enables humans and machines work together apply human intelligence large-scale data at high speed. The objective is classify messages that people post during disasters into set user-defined categories information (e.g., "needs", "damage", etc.) For this purpose, the system continuously ingests from Twitter, processes it (i.e.,...

The use of social media to communicate timely information during crisis situations has become a common practice in recent years. In particular, the one-to-many nature Twitter created an opportunity for stakeholders disseminate crisis-relevant messages, and access vast amounts they may not otherwise have. Our goal is understand what affected populations, response agencies other can expect-and expect-from these data various types disaster situations. Anecdotal evidence suggests that different...

Social network analysis has gained significant attention in recent years, largely due to the success of online social networking and media-sharing sites, consequent availability a wealth data. In spite growing interest, however, there is little understanding potential business applications mining networks. While large body research on different problems methods for mining, gap between techniques developed by community their deployment real-world applications. Therefore impact these still...

Locating timely, useful information during crises and mass emergencies is critical for those forced to make potentially life-altering decisions. As the use of Twitter broadcast such situations becomes more widespread, problem finding it difficult. We describe an approach toward improving recall in sampling communications that can lead greater situational awareness crisis situations. First, we create a lexicon crisis-related terms frequently appear relevant messages posted different types...

Algorithms and decision making based on Big Data have become pervasive in all aspects of our daily lives (offline online), as they essential tools personal finance, health care, hiring, housing, education, policies. It is therefore societal ethical importance to ask whether these algorithms can be discriminative grounds such gender, ethnicity, or status. turns out that the answer positive: for instance, recent studies context online advertising show ads high-income jobs are presented men...

Abstract Purpose Twitter is a popular microblogging service which has proven, in recent years, its potential for propagating news and information about developing events. The purpose of this paper to focus on the analysis credibility Twitter. our research establish if an automatic discovery process relevant credible events can be achieved. Design/methodology/approach follows supervised learning approach task classification A first classifier decides cascade corresponds newsworthy event. Then...

Web spam can significantly deteriorate the quality of search engine results. Thus there is a large incentive for commercial engines to detect pages efficiently and accurately. In this paper we present detection system that combines link-based content-based features, uses topology graph by exploiting link dependencies among pages. We find linked hosts tend belong same class: either both are or non-spam. demonstrate three methods incorporating into predictions obtained our base classifier: (i)...

In this paper we study the problem of local triangle counting in large graphs. Namely, given a graph G = (V;E) want to estimate as accurately possible number triangles incident every node υ ∈ V graph. The computing global has been considered before, but our knowledge is first that addresses with focus on efficiency issues arising massive distribution and related clustering coefficient can be used many interesting applications. For example, show measures compute help detect presence spamming...

We study the problem of online team formation. consider a setting in which people possess different skills and compatibility among potential members is modeled by social network. A sequence tasks arrives an fashion, each task requires specific set skills. The goal to form new upon arrival task, so that (i) possesses all required (ii) has small communication overhead, (iii) workload performing balanced fairest possible way.

Query logs record the queries and actions of users search engines, as such they contain valuable information about interests, preferences, behavior users, well their implicit feedback to engine results. Mining wealth available in query has many important applications including query-log analysis, user profiling personalization, advertising, recommendation, more.In this paper we introduce query-flow graph, a graph representation interesting knowledge latent querying behavior. Intuitively,...

In this paper we study approximate landmark-based methods for point-to-point distance estimation in very large networks. These involve selecting a subset of nodes as landmarks and computing offline the distances from each node graph to those landmarks. At runtime, when between pair is needed, it can be estimated quickly by combining precomputed distances. We prove that optimal set an NP-hard problem, thus heuristic solutions need employed. therefore explore theoretical insights devise...

We study the problem of correlating micro-blogging activity with stock-market events, defined as changes in price and traded volume stocks. Specifically, we collect messages related to a number companies, search for correlations between events those companies features extracted from messages. The extract can be categorized two groups. Features first group measure overall platform, such posts, re-posts, so on. second properties an induced interaction graph, instance, connected components,...

Research on social networks has exploded over the last decade. To a large extent, this been fueled by spectacular growth of media and online networking sites, which continue grow

During times of disasters online users generate a significant amount data, some which are extremely valuable for relief efforts. In this paper, we study the nature social-media content generated during two different natural disasters. We also train model based on conditional random fields to extract information from such content. evaluate our techniques over datasets through set carefully designed experiments. test methods non-disaster dataset show that extraction is useful extracting...

In this work, we define and solve the Fair Top-k Ranking problem, in which want to determine a subset of k candidates from large pool n >> candidates, maximizing utility (i.e., select "best" candidates) subject group fairness criteria. Our ranked definition extends using standard notion protected groups is based on ensuring that proportion every prefix top-k ranking remains statistically above or indistinguishable given minimum. Utility operationalized two ways: (i) candidate included...

This paper presents a study of the life cycle news articles posted online. We describe interplay between website visitation patterns and social media reactions to content. show that we can use this hybrid observation method characterize distinct classes articles. also find help predict future early accurately. validate our methods using qualitative analysis as well quantitative on data from large international network, for set generating more than 3,000,000 visits 200,000 reactions. it is...