Are you talking to me? An analysis of journalism conversation on social media

Social media has become a key medium for discussion and dissemination of news stories, fuelled by the low barrier to entry and the ease of interaction. News stories may be propagated through these networks either by official news organisation accounts, by individual journalists or by members of the public, through link sharing, endorsing or commenting. This preliminary research aims to show how computational analysis of large-scale data-sets allows us to investigate the means by which news stories are spread through social media, and how the conversation around them is shaped by journalists and news organisations. Through the capture of more than 11 million tweets relating to 2303 Twitter accounts connected to journalism and news organisations, we are able to analyse the conversation within and around journalism, examining who spreads information about news articles and who interacts in the discussion around them. Capturing the tweets of news organisations and journalists and the replies and retweets of these micro-blogs allows us to build a rich picture of interaction around news media

Birds of a feather locate together? Foursquare checkins and personality homophily

In this paper we consider whether people with similar personality traits have a preference for common locations. Due to the difficulty in tracking and categorising the places that individuals choose to visit, this is largely unexplored. However, the recent popularity of location-based social networks (LBSNs) provides a means to gain new insight into this question through checkins - records that are made by LBSN users of their presence at specific street level locations. A web-based participatory survey was used to collect the personality traits and checkin behaviour of 174 anonymous users, who, through their common check-ins, formed a network with 5373 edges and an approximate edge density of 35%. We assess the degree of overlap in personality traits for users visiting common locations, as detected by user checkins. We find that people with similar high levels of conscientiousness, openness or agreeableness tended to have checked-in locations in common. The findings for extraverts were unexpected in that they did not provide evidence of individuals assorting at the same locations, contrary to predictions. Individuals high in neuroticism were in line with expectations, they did not tend to have locations in common. Unanticipated results concerning disagreeableness are of particular interest and suggest that different venue types and distinctive characteristics may act as attractors for people with particularly selective tendencies. These findings have important implications for decision-making and location

e-Social Science and Evidence-Based Policy Assessment : Challenges and Solutions

Peer reviewedPreprin

Personality and location-based social networks

Location-based social networks (LBSNs) are a recent phenomenon for sharing a presence at everyday locations with others and have the potential to give new insights into human behaviour. To date, due to barriers in data collection, there has been little research into how our personality relates to the categories of place that we visit. Using the Foursquare LBSN, we have released a web-based participatory application that examines the personality characteristics and checkin behaviour of volunteer Foursquare users. Over a four-month period, we examine the behaviour and the “Big Five” personality traits of 174 anonymous users who had collectively checked in 487,396 times at 119,746 venues. Significant correlations are found for Conscientiousness, Openness and Neuroticism. In contrast to some previous findings about online social networks, Conscientiousness is positively correlated with LBSN usage. Openness correlates mainly with location-based variables (average distance between venues visited, venue popularity, number of checkins at sociable venues). For Neuroticism, further negative correlations are found (number of venues visited, number of sociable venues visited). No correlations are found for the other personality traits, which is surprising for Extroversion. The study concludes that personality traits help to explain individual differences in LBSN usage and the type of places visited

Human content filtering in Twitter: The influence of metadata

Social micro-blogging systems such as Twitter are designed for rapid and informal communication from a large potential number of participants. Due to the volume of content received, human users must typically skim their timeline of received content and exercise judgement in selecting items for consumption, necessitating a selection process based on heuristics and content meta-data. This selection process is not well understood, yet is important due to its potential use in content management systems. In this research we have conducted an open online experiment in which participants are shown quantitative and qualitative meta-data describing two pieces of Twitter content. Without revealing the text of the tweet, participants are asked to make a selection. We observe the decisions made from 239 surveys and discover insights into human behaviour on decision making for content selection. We find that for qualitative meta-data consumption decisions are driven by online friendship and for quantitative meta-data the largest numerical value presented influences choice. Overall, the ‘number of retweets’ is found to be the most influential quantitative meta-data, while displaying multiple cues about an author's identity provides the strongest qualitative meta-data. When both quantitative and qualitative meta-data is presented, it is the qualitative meta-data (friendship information) that drives selection. The results are consistent with application of the Recognition heuristic, which postulates that when faced with constrained decision-making, humans will tend to exercise judgement based on cues representing familiarity. These findings are useful for future interface design for content filtering and recommendation systems

Desynchronization and Wave Pattern Formation in MPI-Parallel and Hybrid Memory-Bound Programs

Analytic, first-principles performance modeling of distributed-memory parallel codes is notoriously imprecise. Even for applications with extremely regular and homogeneous compute-communicate phases, simply adding communication time to computation time does often not yield a satisfactory prediction of parallel runtime due to deviations from the expected simple lockstep pattern caused by system noise, variations in communication time, and inherent load imbalance. In this paper, we highlight the specific cases of provoked and spontaneous desynchronization of memory-bound, bulk-synchronous pure MPI and hybrid MPI+OpenMP programs. Using simple microbenchmarks we observe that although desynchronization can introduce increased waiting time per process, it does not necessarily cause lower resource utilization but can lead to an increase in available bandwidth per core. In case of significant communication overhead, even natural noise can shove the system into a state of automatic overlap of communication and computation, improving the overall time to solution. The saturation point, i.e., the number of processes per memory domain required to achieve full memory bandwidth, is pivotal in the dynamics of this process and the emerging stable wave pattern. We also demonstrate how hybrid MPI-OpenMP programming can prevent desirable desynchronization by eliminating the bandwidth bottleneck among processes. A Chebyshev filter diagonalization application is used to demonstrate some of the observed effects in a realistic setting.Comment: 18 pages, 8 figure

Analysis of European colour vision certification requirements for air traffic control officers

The advantages of using colour in large-field, visual displays have been investigated with emphasis on ATC applications. This study examined and quantified the relationship between severity of colour vision loss in congenital deficiency and the corresponding changes in visual performance. Analysis of current colour assessment protocols and the current findings provide the basis for a new system of colour categories that can be enforced. The report also describes how a colour category can be selected for a given occupational task by examining the colour-related requirements and the applicant’s class of colour deficiency

Giga-Hertz quantized charge pumping in bottom gate defined InAs nanowire quantum dots

Semiconducting nanowires (NWs) are a versatile, highly tunable material platform at the heart of many new developments in nanoscale and quantum physics. Here, we demonstrate charge pumping, i.e., the controlled transport of individual electrons through an InAs NW quantum dot (QD) device at frequencies up to $1.3\,$GHz. The QD is induced electrostatically in the NW by a series of local bottom gates in a state of the art device geometry. A periodic modulation of a single gate is enough to obtain a dc current proportional to the frequency of the modulation. The dc bias, the modulation amplitude and the gate voltages on the local gates can be used to control the number of charges conveyed per cycle. Charge pumping in InAs NWs is relevant not only in metrology as a current standard, but also opens up the opportunity to investigate a variety of exotic states of matter, e.g. Majorana modes, by single electron spectroscopy and correlation experiments.Comment: 21 page

Challenging Methods and Results Obtained from User-Generated Content in Barcelona’s Public Open Spaces

User-generated content (UGC) provides useful resources for academics, technicians and policymakers to obtain and analyse results in order to improve lives of individuals in urban settings. User-generated content comes from people who voluntarily contribute data, information, or media that then appears in a way which can be viewed by others; usually on the Web. However, to date little is known about how complex methodologies for getting results are subject to methodology-formation errors, personal data protection, and reliability of outcomes. Different researches have been approaching to inquire big data methods for a better understanding of social groups for planners and economic needs. In this chapter, through UGC from Tweets of users located in Barcelona, we present different research experiments. Data collection is based on the use of REST API; while analysis and representation of UGC follow different ways of processing and providing a plurality of information. The first objective is to study the results at a different geographical scale, Barcelona’s Metropolitan Area and at two Public Open Spaces (POS) in Barcelona, Enric Granados Street and the area around the Fòrum de les Cultures; during similar days in two periods of time - in January of 2015 and 2017. The second objective is intended to better understand how different types of POS’ Twitter-users draw urban patterns. The Origin-Destination patterns generated illustrate new social behaviours, addressed to multifunctional uses. This chapter aims to be influential in the use of UGC analysis for planning purposes and to increase quality of life