Pub crawling at scale:tapping untappd to explore social drinking

There has been a recent surge of research looking at the reporting of food consumption on social media. The topic of alcohol consumption, however, remains poorly investigated. Social media has the potential to shed light on a topic that, traditionally, is difficult to collect fine-grained information on. One social app stands out in this regard: Untappd is an app that allows users to ‘check-in’ their consumption of beers. It operates in a similar fashion to other location-based applications, but is specifically tailored to the collection of information on beer consumption. In this paper, we explore beer consumption through the lens of social media. We crawled Untappd in real time over a period of 112 days, across 40 cities in the United States and Europe. Using this data, we shed light on the drinking habits of over 369k users. We focus on per-user and per-city characterisation, highlighting key behavioural trends

Performance engineering of hybrid message passing + shared memory programming on multi-core clusters

The hybrid message passing + shared memory programming model combines two parallel programming styles within the same application in an effort to improve the performance and efficiency of parallel codes on modern multi-core clusters. This thesis presents a performance study of this model as it applies to two Molecular Dynamics (MD) applications. Both a large scale production MD code and a smaller scale example MD code have been adapted from existing message passing versions by adding shared memory parallelism to create hybrid message passing + shared memory applications. The performance of these hybrid applications has been investigated on different multi-core clusters and compared with the original pure message passing codes. This performance analysis reveals that the hybrid message passing + shared memory model provides performance improvements under some conditions, while the pure message passing model provides better performance in others. Typically, when running on small numbers of cores the pure message passing model provides better performance than the hybrid message passing + shared memory model, as hybrid performance suffers due to increased overheads from the use of shared memory constructs. However, when running on large numbers of cores the hybrid model performs better as these shared memory overheads are minimised while the pure message passing code suffers from increased communication overhead. These results depend on the interconnect used. Hybrid message passing + shared memory molecular dynamics codes are shown to exhibit different communication profiles from their pure message passing versions and this is revealed to be a large factor in the performance difference between pure message passing and hybrid message passing + shared memory codes. An extension of this result shows that the choice of interconnection fabric used in a multi-core cluster has a large impact on the performance difference between the pure message passing and the hybrid code. The factors affecting the performance of the applications have been analytically examined in an effort to describe, generalise and predict the performance of both the pure message passing and hybrid message passing + shared memory codes

Performance analysis of a hybrid MPI/OpenMP application on multi-core clusters

The mixing of shared memory and message passing programming models within a single application has often been suggested as a method for improving scientific application performance on clusters of shared memory or multi-core systems. DL_POLY, a large scale molecular dynamics application programmed using message passing programming has been modified to add a layer of shared memory threading and the performance analysed on two multi-core clusters. At lower processor numbers, the extra overheads from shared memory threading in the hybrid code outweigh performance benefits gained over the pure MPI code. On larger core counts the hybrid model performs better than pure MPI, with reduced communication time decreasing the overall runtime

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

Pub crawling at scale: tapping Untappd to explore social drinking

There has been a recent surge of research looking at the reporting of food consumption on social media. The topic of alcohol consumption, however, remains poorly investigated. Social media has the potential to shed light on a topic that, traditionally, is difficult to collect fine-grained information on. One social app stands out in this regard: Untappd is an app that allows users to ‘check-in’ their consumption of beers. It operates in a similar fashion to other location-based applications, but is specifically tailored to the collection of information on beer consumption. In this paper, we explore beer consumption through the lens of social media. We crawled Untappd in real time over a period of 112 days, across 40 cities in the United States and Europe. Using this data, we shed light on the drinking habits of over 369k users. We focus on per-user and per-city characterisation, highlighting key behavioural trends

Hybrid message-passing and shared-memory programming in a molecular dynamics application on multicore clusters

Hybrid programming, whereby shared-memory and message-passing programming techniques are combined within a single parallel application, has often been discussed as a method for increasing code performance on clusters of symmetric multiprocessors (SMPs). This paper examines whether the hybrid model brings any performance benefits for clusters based on multicore processors. A molecular dynamics application has been parallelized using both MPI and hybrid MPI/OpenMP programming models. The performance of this application has been examined on two high-end multicore clusters using both Infiniband and Gigabit Ethernet interconnects. The hybrid model has been found to perform well on the higher-latency Gigabit Ethernet connection, but offers no performance benefit on low-latency Infiniband interconnects. The changes in performance are attributed to the differing communication profiles of the hybrid and MPI codes

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

An open reproducible framework for the study of the iterated prisoner's dilemma

The Axelrod library is an open source Python package that allows for reproducible game theoretic research into the Iterated Prisoner's Dilemma. This area of research began in the 1980s but suffers from a lack of documentation and test code. The goal of the library is to provide such a resource, with facilities for the design of new strategies and interactions between them, as well as conducting tournaments and ecological simulations for populations of strategies. With a growing collection of 139 strategies, the library is a also a platform for an original tournament that, in itself, is of interest to the game theoretic community. This paper describes the Iterated Prisoner's Dilemma, the Axelrod library and its development, and insights gained from some novel research.Comment: 11 pages, Journal of Open Research Software 4.1 (2016