Finding unexplained human behaviors in Social Networks

Detection of human behavior in On-line Social Networks (OSNs) has become a very important challenge for a wide range of appli- cations, such as security, marketing, parent controls and so on, opening a wide range of novel research areas, which have not been fully addressed yet. In this paper, we present a two-stage method for finding unexplained (and potentially anomalous) behaviors in social networks. First, we use Markov chains to automatically learn from the social network graph a number of models of human behaviors (normal behaviors); the second stage applies an activity detection framework based on the concept of possible words to detect all unexplained activities with respect to the well-known behaviors. Some preliminary experiments using Facebook data show the approach efficiency and effectiveness. Copyright © (2014) by Universita Reggio Calabria & Centro di Competenza (ICT-SUD) All rights reserved

Applying Item Response Theory (IRT) Modeling to an Observational Measure of Childhood Pragmatics: The Pragmatics Observational Measure-2

Assessment of pragmatic language abilities of children is important across a number of childhood developmental disorders including ADHD, language impairment and Autism Spectrum Disorder. The Pragmatics Observational Measure (POM) was developed to investigate children's pragmatic skills during play in a peer-peer interaction. To date, classic test theory methodology has reported good psychometric properties for this measure, but the POM has yet to be evaluated using item response theory. The aim of this study was to evaluate the POM using Rasch analysis. Person and item fit statistics, response scale, dimensionality of the scale and differential item functioning were investigated. Participants included 342 children aged 5-11 years from New Zealand; 108 children with ADHD were playing with 108 typically developing peers and 126 typically developing age, sex and ethnic matched peers played in dyads in the control group. Video footage of this interaction was recorded and later analyzed by an independent rater unknown to the children using the POM. Rasch analysis revealed that the rating scale was ordered and used appropriately. The overall person (0.97) and item (0.99) reliability was excellent. Fit statistics for four individual items were outside acceptable parameters and were removed. The dimensionality of the measure showed two distinct elements (verbal and non-verbal pragmatic language) of a unidimensional construct. These findings have led to a revision of the first edition of POM, now called the POM-2. Further empirical work investigating the responsiveness of the POM-2 and its utility in identifying pragmatic language impairments in other childhood developmental disorders is recommended

Gender Differences in Participation and Reward on Stack Overflow

Programming is a valuable skill in the labor market, making the underrepresentation of women in computing an increasingly important issue. Online question and answer platforms serve a dual purpose in this field: they form a body of knowledge useful as a reference and learning tool, and they provide opportunities for individuals to demonstrate credible, verifiable expertise. Issues, such as male-oriented site design or overrepresentation of men among the site's elite may therefore compound the issue of women's underrepresentation in IT. In this paper we audit the differences in behavior and outcomes between men and women on Stack Overflow, the most popular of these Q&A sites. We observe significant differences in how men and women participate in the platform and how successful they are. For example, the average woman has roughly half of the reputation points, the primary measure of success on the site, of the average man. Using an Oaxaca-Blinder decomposition, an econometric technique commonly applied to analyze differences in wages between groups, we find that most of the gap in success between men and women can be explained by differences in their activity on the site and differences in how these activities are rewarded. Specifically, 1) men give more answers than women and 2) are rewarded more for their answers on average, even when controlling for possible confounders such as tenure or buy-in to the site. Women ask more questions and gain more reward per question. We conclude with a hypothetical redesign of the site's scoring system based on these behavioral differences, cutting the reputation gap in half

Mitigating Insider Sabotage and Espionage: A Review of the United States Air Force\u27s Current Posture

The security threat from malicious insiders affects all organizations. Mitigating this problem is quite difficult due to the fact that (1) there is no definitive profile for malicious insiders, (2) organizations have placed trust in these individuals, and (3) insiders have a vast knowledge of their organization’s personnel, security policies, and information systems. The purpose of this research is to analyze to what extent the United States Air Force (USAF) security policies address the insider threat problem. The policies are reviewed in terms of how well they align with best practices published by the Carnegie Mellon University Computer Emergency Readiness Team and additional factors this research deems important, including motivations, organizational priorities, and social networks. Based on the findings of the policy review, this research offers actionable recommendations that the USAF could implement in order to better prevent, detect, and respond to malicious insider attacks. The most important course of action is to better utilize its workforce. All personnel should be trained on observable behaviors that can be precursors to malicious activity. Additionally, supervisors need to be empowered as the first line of defense, monitoring for stress, unmet expectations, and disgruntlement. In addition, this research proposes three new best practices regarding (1) screening for prior concerning behaviors, predispositions, and technical incidents, (2) issuing sanctions for inappropriate technical acts, and (3) requiring supervisors to take a proactive role

A contextual behavioral approach to the study of (persecutory) delusions

Throughout the past century the topic of delusions has mainly been studied by researchers operating at the mental level of analysis. According to this perspective, delusional beliefs, as well as their emergence and persistence, stem from an interplay between (dysfunctional) mental representations and processes. Our paper aims to provide a starting point for researchers and clinicians interested in examining the topic of delusions from a functional-analytic perspective. We begin with a brief review of the research literature with a particular focus on persecutory delusions. Thereafter we introduce Contextual Behavioral Science (CBS), Relational Frame Theory (RFT) and a behavioral phenomenon known as arbitrarily applicable relational responding (AARR). Drawing upon AARR, and recent empirical developments within CBS, we argue that (persecutory) delusions may be conceptualized, studied and influenced using a functional-analytic approach. We consider future directions for research in this area as well as clinical interventions aimed at influencing delusions and their expression

A Hypergraph Data Model for Expert-Finding in Multimedia Social Networks

Online Social Networks (OSNs) have found widespread applications in every area of our life. A large number of people have signed up to OSN for different purposes, including to meet old friends, to choose a given company, to identify expert users about a given topic, producing a large number of social connections. These aspects have led to the birth of a new generation of OSNs, called Multimedia Social Networks (MSNs), in which user-generated content plays a key role to enable interactions among users. In this work, we propose a novel expert-finding technique exploiting a hypergraph-based data model for MSNs. In particular, some user-ranking measures, obtained considering only particular useful hyperpaths, have been profitably used to evaluate the related expertness degree with respect to a given social topic. Several experiments on Last.FM have been performed to evaluate the proposed approach's effectiveness, encouraging future work in this direction for supporting several applications such as multimedia recommendation, influence analysis, and so on

Validation of the Commercial Sexual Exploitation-Identification Tool

Trafficked youth are typically not identified until years after their exploitation has begun. In order to protect youth from prolonged abuse and violence and get them help, exploitation must be recognized as early as possible. To make this possible, service providers and other professionals who work with youth need a validated screening tool to aid in accurately detecting exploitation.the cse-it is an evidence based toolIn 2014, WestCoast Children's Clinic developed the Commercial Sexual Exploitation – Identification Tool (CSE-IT) with the input of over 100 survivors and service providers. In 2016, we validated the CSE-IT with data from a 15-month pilot to ensure that it accurately identifies youth who have clear indicators of exploitation. Since 2015 we have worked collaboratively with 77 agencies in 3 states to use the CSE-IT. As of June 2017, WestCoast has trained 4,000 service providers to recognize the signs of exploitation. These providers screened 12,500 youth and identified 1,500 youth with clear indicators of exploitation

Causality in Political Networks

As the study of political networks becomes more common in political science, greater attention to questions of causality is warranted. This essay explores competing visions of causality in political networks. Independent essays address issues of statistical model specification, identification of multi-step personal influence, measurement error, causality in historical perspective, and the insights of field experiments. These essays do not agree entirely on the nature of causality in political networks, though they commonly take seriously concerns regarding homophily, time- consistency, and the uniqueness of political network data. Serious consideration of these methodological issues promises to enhance the value-added of network analysis in the study of politics

Discrimination in a Low-Wage Labor Market: A Field Experiment

Decades of racial progress have led some researchers and policymakers to doubt that discrimination remains an important cause of economic inequality. To study contemporary discrimination we conducted a field experiment in the low-wage labor market of New York City. The experiment recruited white, black, and Latino job applicants, called testers, who were matched on demographic characteristics and interpersonal skills. The testers were given equivalent resumes and sent to apply in tandem for hundreds of entry-level jobs. Our results show that black applicants were half as likely to receive a callback or job offer relative to equally qualified whites. In fact, black and Latino applicants with clean backgrounds fared no better than a white applicant just released from prison. Additional qualitative evidence from our testers' experiences further illustrates the multiple points at which employment trajectories can be deflected by various forms of racial bias. Together these results point to the subtle but systematic forms of discrimination that continue to shape employment opportunities for low-wage workers.race, field experiment, discrimination, labor markets