An Army of Me: Sockpuppets in Online Discussion Communities

In online discussion communities, users can interact and share information and opinions on a wide variety of topics. However, some users may create multiple identities, or sockpuppets, and engage in undesired behavior by deceiving others or manipulating discussions. In this work, we study sockpuppetry across nine discussion communities, and show that sockpuppets differ from ordinary users in terms of their posting behavior, linguistic traits, as well as social network structure. Sockpuppets tend to start fewer discussions, write shorter posts, use more personal pronouns such as "I", and have more clustered ego-networks. Further, pairs of sockpuppets controlled by the same individual are more likely to interact on the same discussion at the same time than pairs of ordinary users. Our analysis suggests a taxonomy of deceptive behavior in discussion communities. Pairs of sockpuppets can vary in their deceptiveness, i.e., whether they pretend to be different users, or their supportiveness, i.e., if they support arguments of other sockpuppets controlled by the same user. We apply these findings to a series of prediction tasks, notably, to identify whether a pair of accounts belongs to the same underlying user or not. Altogether, this work presents a data-driven view of deception in online discussion communities and paves the way towards the automatic detection of sockpuppets.Comment: 26th International World Wide Web conference 2017 (WWW 2017

Sensitivity of Species Habitat-Relationship Model Performance to Factors of Scale

Researchers have come to different conclusions about the usefulness of habitat-relationship models for predicting species presence or absence. This difference frequently stems from a failure to recognize the effects of spatial scales at which the models are applied. We examined the effects of model complexity, spatial data resolution, and scale of application on the performance of bird habitat relationship (BHR) models on the Craig Mountain Wildlife Management Area and on the Idaho portion of the U.S. Forest Service\u27s Northern Region. We constructed and tested BHR models for 60 bird species detected on the study areas. The models varied by three levels of complexity (amount of habitat information) and three spatial data resolutions (0.09 ha, 4 ha, 10 ha). We tested these models at two levels of analysis: the site level (a homogeneous area \u3c0.5 ha) and cover-type level (an aggregation of many similar sites of a similar land-cover type), using correspondence between model predictions and species detections to calculate kappa coefficients of agreement. Model performance initially increased as models became more complex until a point was reached where omission errors increased at a rate greater than the rate at which commission errors were decreasing. Heterogeneity of the study areas appeared to influence the effect of model complexity. Changes in model complexity resulted in a greater decrease in commission error than increase in omission error. The effect of spatial data resolution on the performance of BHR models was influenced by the variability of the study area. BHR models performed better at cover-type levels of analysis than at the site level for both study areas. Correct-presence estimates (1 − minus percentage omission error) decreased slightly as number of species detections increased on each study area. Correct-absence estimates (1 − percentage commission error) increased as number of species detections increased on each study area. This suggests that a large number of detections may be necessary to achieve reliable estimates of model accuracy

User Intent Prediction in Information-seeking Conversations

Conversational assistants are being progressively adopted by the general population. However, they are not capable of handling complicated information-seeking tasks that involve multiple turns of information exchange. Due to the limited communication bandwidth in conversational search, it is important for conversational assistants to accurately detect and predict user intent in information-seeking conversations. In this paper, we investigate two aspects of user intent prediction in an information-seeking setting. First, we extract features based on the content, structural, and sentiment characteristics of a given utterance, and use classic machine learning methods to perform user intent prediction. We then conduct an in-depth feature importance analysis to identify key features in this prediction task. We find that structural features contribute most to the prediction performance. Given this finding, we construct neural classifiers to incorporate context information and achieve better performance without feature engineering. Our findings can provide insights into the important factors and effective methods of user intent prediction in information-seeking conversations.Comment: Accepted to CHIIR 201

Stratus Ocean Reference Station (20˚S, 85˚W), mooring recovery and deployment cruise R/V Ronald H. Brown cruise 05-05, September 26, 2005–October 21, 2005

The Ocean Reference Station at 20°S, 85°W under the stratus clouds west of northern Chile is being maintained to provide ongoing, climate-quality records of surface meteorology, of air-sea fluxes of heat, freshwater, and momentum, and of upper ocean temperature, salinity, and velocity variability. The Stratus Ocean Reference Station (ORS Stratus) is supported by the National Oceanic and Atmospheric Administration’s (NOAA) Climate Observation Program. It is recovered and redeployed annually, with cruises that have come between October and December. During the October 2005 cruise of NOAA’s R/V Ronald H. Brown to the ORS Stratus site, the primary activities were recovery of the WHOI surface mooring that had been deployed in December 2004, deployment of a new WHOI surface mooring at that site, in-situ calibration of the buoy meteorological sensors by comparison with instrumentation put on board by staff of the NOAA Environmental Technology Laboratory (ETL), and observations of the stratus clouds and lower atmosphere by NOAA ETL. The ORS Stratus buoys are equipped with two Improved Meteorological (IMET) systems, which provide surface wind speed and direction, air temperature, relative humidity, barometric pressure, incoming shortwave radiation, incoming longwave radiation, precipitation rate, and sea surface temperature. The IMET data are made available in near real time using satellite telemetry. The mooring line carries instruments to measure ocean salinity, temperature, and currents. The ETL instrumentation used during the 2005 cruise included cloud radar, radiosonde ballons, and sensors for mean and turbulent surface meteorology. In addition, two technicians from the University of Concepcion collected water samples for chemical analysis. Finally, the cruise hosted a teacher participating in NOAA’s Teacher at Sea Program.Funding was provided by the National Oceanic and Atmospheric Administration under Grant No. NA17RJ1223 and the Cooperative Institute for Climate and Ocean Research (CICOR)

Structural representations: causally relevant and different from detectors

This paper centers around the notion that internal, mental representations are grounded in structural similarity, i.e., that they are so-called S-representations. We show how S-representations may be causally relevant and argue that they are distinct from mere detectors. First, using the neomechanist theory of explanation and the interventionist account of causal relevance, we provide a precise interpretation of the claim that in S-representations, structural similarity serves as a ‘‘fuel of success’’, i.e., a relation that is exploitable for the representation using system. Then, we discuss crucial differences between S-representations and indicators or detectors, showing that—contrary to claims made in the literature—there is an important theoretical distinction to be drawn between the two

Interacting with Fictions:The Role of Pretend Play in Theory of Mind Acquisition

Pretend play is generally considered to be a developmental landmark in Theory of Mind acquisition. The aim of the present paper is to offer a new account of the role of pretend play in Theory of Mind development. To this end I combine Hutto and Gallagher’s account of social cognition development with Matravers’ recent argument that the cognitive processes involved in engagement with narratives are neutral regarding fictionality. The key contribution of my account is an analysis of pretend play as interaction with fictions. I argue that my account offers a better explanation of existing empirical data on the development of children’s pretend play and Theory of Mind than the competing theories from Leslie, Perner and Harris

Making healthy eating and physical activity policy practice: process evaluation of a group randomized controlled intervention in afterschool programs

This study describes the link between level of implementation and outcomes from an intervention to increase afterschool programs’ (ASPs) achievement of healthy eating and physical activity (HE-PA) Standards. Ten intervention ASPs implemented the Strategies-To-Enhance-Practice (STEPs), a multi-component, adaptive intervention framework identifying factors essential to meeting HE-PA Standards, while 10 control ASPs continued routine practice. All programs, intervention and control, were assigned a STEPs for HE-PA index score based on implementation. Mixed-effects linear regressions showed high implementation ASPs had the greatest percentage of boys and girls achieving 30 min of moderate-to-vigorous physical activity (47.3 and 29.3%), followed by low implementation ASPs (41.3 and 25.0%), and control ASPs (34.8 and 18.5%). For healthy eating, high/low implementation programs served fruits and vegetables an equivalent number of days, but more days than control programs (74.0 and 79.1% of days versus 14.2%). A similar pattern emerged for the percent of days sugar-sweetened foods and beverages were served, with high and low implementation programs serving sugar-sweetened foods (8.0 and 8.4% of days versus 52.2%), and beverages (8.7 and 2.9% of days versus 34.7%) equivalently, but less often than control programs. Differences in characteristics and implementation of STEPs for HE-PA between high/low implementers were also identified

Landscape Movements of Migratory Birds and Bats Reveal an Expanded Scale of Stopover

Many species of birds and bats undertake seasonal migrations between breeding and over-wintering sites. En-route, migrants alternate periods of flight with time spent at stopover – the time and space where individuals rest and refuel for subsequent flights. We assessed the spatial scale of movements made by migrants during stopover by using an array of automated telemetry receivers with multiple antennae to track the daily location of individuals over a geographic area ∼20×40 km. We tracked the movements of 322 individuals of seven migratory vertebrate species (5 passerines, 1 owl and 1 bat) during spring and fall migratory stopover on and adjacent to a large lake peninsula. Our results show that many individuals leaving their capture site relocate within the same landscape at some point during stopover, moving as much as 30 km distant from their site of initial capture. We show that many apparent nocturnal departures from stopover sites are not a resumption of migration in the strictest sense, but are instead relocations that represent continued stopover at a broader spatial scale

The influence of personality and ability on undergraduate teamwork and team performance

The ability to work effectively on a team is highly valued by employers, and collaboration among students can lead to intrinsic motivation, increased persistence, and greater transferability of skills. Moreover, innovation often arises from multidisciplinary teamwork. The influence of personality and ability on undergraduate teamwork and performance is not comprehensively understood. An investigation was undertaken to explore correlations between team outcomes, personality measures and ability in an undergraduate population. Team outcomes included various self-, peer- and instructor ratings of skills, performance, and experience. Personality measures and ability involved the Five-Factor Model personality traits and GPA. Personality, GPA, and teamwork survey data, as well as instructor evaluations were collected from upper division team project courses in engineering, business, political science, and industrial design at a large public university. Characteristics of a multidisciplinary student team project were briefly examined. Personality, in terms of extraversion scores, was positively correlated with instructors’ assessment of team performance in terms of oral and written presentation scores, which is consistent with prior research. Other correlations to instructor-, students’ self- and peer-ratings were revealed and merit further study. The findings in this study can be used to understand important influences on successful teamwork, teamwork instruction and intervention and to understand the design of effective curricula in this area moving forward