34,615 research outputs found
Measuring the effect of node aggregation on community detection
Many times the nodes of a complex network, whether deliberately or not, are
aggregated for technical, ethical, legal limitations or privacy reasons. A
common example is the geographic position: one may uncover communities in a
network of places, or of individuals identified with their typical geographical
position, and then aggregate these places into larger entities, such as
municipalities, thus obtaining another network. The communities found in the
networks obtained at various levels of aggregation may exhibit various degrees
of similarity, from full alignment to perfect independence. This is akin to the
problem of ecological and atomic fallacies in statistics, or to the Modified
Areal Unit Problem in geography. We identify the class of community detection
algorithms most suitable to cope with node aggregation, and develop an index
for aggregability, capturing to which extent the aggregation preserves the
community structure. We illustrate its relevance on real-world examples (mobile
phone and Twitter reply-to networks). Our main message is that any
node-partitioning analysis performed on aggregated networks should be
interpreted with caution, as the outcome may be strongly influenced by the
level of the aggregation.Comment: 12 pages, 5 figure
Virtual Communities and Patterns of Social Interactions in ‘Tech City’
The impact of social media and Web 2.0 on socioeconomic behaviour in the physical space of the built environment had recently become a matter of intense debate in social sciences and human geography. This paper examines the relationship between the configurations of urban space from the perspective of 'space syntax' theory by Hillier and Hanson (1984) and the configurations of social networks in Twitter, whilst focusing on the technology start-up cluster in 'Tech City' London. Where there has been arguments made for a strong correlation between twitter ties in businesses and physical distance, this research is focused on the borough scale aiming to outline a relationship between the configurations of streets and the virtual and socioeconomic attributes of start-up businesses. The paper reports a moderate relationship between indices of centrality in twitter network and its correspondent measure in street networks. In addition, the research yields global and temporal patterns of relationships with land uses and land values. The paper concludes by reflecting on how the configurations of twitter Tech-City community are present in the physical medium, where short and long links define the local and global part-whole relationship between Tech-City and other communities
Traveling Trends: Social Butterflies or Frequent Fliers?
Trending topics are the online conversations that grab collective attention
on social media. They are continually changing and often reflect exogenous
events that happen in the real world. Trends are localized in space and time as
they are driven by activity in specific geographic areas that act as sources of
traffic and information flow. Taken independently, trends and geography have
been discussed in recent literature on online social media; although, so far,
little has been done to characterize the relation between trends and geography.
Here we investigate more than eleven thousand topics that trended on Twitter in
63 main US locations during a period of 50 days in 2013. This data allows us to
study the origins and pathways of trends, how they compete for popularity at
the local level to emerge as winners at the country level, and what dynamics
underlie their production and consumption in different geographic areas. We
identify two main classes of trending topics: those that surface locally,
coinciding with three different geographic clusters (East coast, Midwest and
Southwest); and those that emerge globally from several metropolitan areas,
coinciding with the major air traffic hubs of the country. These hubs act as
trendsetters, generating topics that eventually trend at the country level, and
driving the conversation across the country. This poses an intriguing
conjecture, drawing a parallel between the spread of information and diseases:
Do trends travel faster by airplane than over the Internet?Comment: Proceedings of the first ACM conference on Online social networks,
pp. 213-222, 201
Citizens and Institutions as Information Prosumers. The Case Study of Italian Municipalities on Twitter
The aim of this paper is to address changes in public communication following the advent of Internet social networking tools and the emerging web 2.0 technologies which are providing new ways of sharing information and knowledge. In particular public administrations are called upon to reinvent the governance of public affairs and to update the means for interacting with their communities. The paper develops an analysis of the distribution, diffusion and performance of the official profiles on Twitter adopted by the Italian municipalities (comuni) up to November 2013. It aims to identify the patterns of spatial distribution and the drivers of the diffusion of Twitter profiles; the performance of the profiles through an aggregated index, called the Twitter performance index (Twiperindex), which evaluates the profiles' activity with reference to the gravitational areas of the municipalities in order to enable comparisons of the activity of municipalities with different demographic sizes and functional roles. The results show that only a small portion of innovative municipalities have adopted Twitter to enhance e-participation and e-governance and that the drivers of the diffusion seem to be related either to past experiences and existing conditions (i.e. civic networks, digital infrastructures) developed over time or to strong local community awareness. The better performances are achieved mainly by small and medium-sized municipalities. Of course, the phenomenon is very new and fluid, therefore this analysis should be considered as a first step in ongoing research which aims to grasp the dynamics of these new means of public communication
Diffusion of Lexical Change in Social Media
Computer-mediated communication is driving fundamental changes in the nature
of written language. We investigate these changes by statistical analysis of a
dataset comprising 107 million Twitter messages (authored by 2.7 million unique
user accounts). Using a latent vector autoregressive model to aggregate across
thousands of words, we identify high-level patterns in diffusion of linguistic
change over the United States. Our model is robust to unpredictable changes in
Twitter's sampling rate, and provides a probabilistic characterization of the
relationship of macro-scale linguistic influence to a set of demographic and
geographic predictors. The results of this analysis offer support for prior
arguments that focus on geographical proximity and population size. However,
demographic similarity -- especially with regard to race -- plays an even more
central role, as cities with similar racial demographics are far more likely to
share linguistic influence. Rather than moving towards a single unified
"netspeak" dialect, language evolution in computer-mediated communication
reproduces existing fault lines in spoken American English.Comment: preprint of PLOS-ONE paper from November 2014; PLoS ONE 9(11) e11311
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