16,169 research outputs found
The network structure of visited locations according to geotagged social media photos
Businesses, tourism attractions, public transportation hubs and other points
of interest are not isolated but part of a collaborative system. Making such
collaborative network surface is not always an easy task. The existence of
data-rich environments can assist in the reconstruction of collaborative
networks. They shed light into how their members operate and reveal a potential
for value creation via collaborative approaches. Social media data are an
example of a means to accomplish this task. In this paper, we reconstruct a
network of tourist locations using fine-grained data from Flickr, an online
community for photo sharing. We have used a publicly available set of Flickr
data provided by Yahoo! Labs. To analyse the complex structure of tourism
systems, we have reconstructed a network of visited locations in Europe,
resulting in around 180,000 vertices and over 32 million edges. An analysis of
the resulting network properties reveals its complex structure.Comment: 8 pages, 3 figure
Survival through networks: the 'grip' of the administrative links in the Russian post-Soviet context
© 2014 Taylor & Francis. Based on an analysis of the post-Soviet transformation experience of four defence sector organizations in a Russian region where the defence sector occupies a substantial part of the local economy, this article develops a typology of network relationships: Grooved Inter-relationship Patterns (Gr’ip) networks and Fluid Inter-relationship Patterns (Fl’ip) networks. This typology can be applied to a range of transition/emerging market and low system trust contexts. Gr’ip networks, in this case, represent the persisting legacy of the Soviet command-administrative system. Fl’ip networks are here an attempt by the defence companies to link into the civilian supply chains of a developing market economy. This article argues that Gr’ip networks had and still have a crucial role to play in Russian enterprises’ survival and development
Symptoms of complexity in a tourism system
Tourism destinations behave as dynamic evolving complex systems, encompassing
numerous factors and activities which are interdependent and whose
relationships might be highly nonlinear. Traditional research in this field has
looked after a linear approach: variables and relationships are monitored in
order to forecast future outcomes with simplified models and to derive
implications for management organisations. The limitations of this approach
have become apparent in many cases, and several authors claim for a new and
different attitude.
While complex systems ideas are amongst the most promising interdisciplinary
research themes emerged in the last few decades, very little has been done so
far in the field of tourism. This paper presents a brief overview of the
complexity framework as a means to understand structures, characteristics,
relationships, and explores the implications and contributions of the
complexity literature on tourism systems. The objective is to allow the reader
to gain a deeper appreciation of this point of view.Comment: 32 pages, 3 figures, 1 table; accepted in Tourism Analysi
Conflict and Computation on Wikipedia: a Finite-State Machine Analysis of Editor Interactions
What is the boundary between a vigorous argument and a breakdown of
relations? What drives a group of individuals across it? Taking Wikipedia as a
test case, we use a hidden Markov model to approximate the computational
structure and social grammar of more than a decade of cooperation and conflict
among its editors. Across a wide range of pages, we discover a bursty war/peace
structure where the systems can become trapped, sometimes for months, in a
computational subspace associated with significantly higher levels of
conflict-tracking "revert" actions. Distinct patterns of behavior characterize
the lower-conflict subspace, including tit-for-tat reversion. While a fraction
of the transitions between these subspaces are associated with top-down actions
taken by administrators, the effects are weak. Surprisingly, we find no
statistical signal that transitions are associated with the appearance of
particularly anti-social users, and only weak association with significant news
events outside the system. These findings are consistent with transitions being
driven by decentralized processes with no clear locus of control. Models of
belief revision in the presence of a common resource for information-sharing
predict the existence of two distinct phases: a disordered high-conflict phase,
and a frozen phase with spontaneously-broken symmetry. The bistability we
observe empirically may be a consequence of editor turn-over, which drives the
system to a critical point between them.Comment: 23 pages, 3 figures. Matches published version. Code for HMM fitting
available at http://bit.ly/sfihmm ; time series and derived finite state
machines at bit.ly/wiki_hm
Link Prediction in Complex Networks: A Survey
Link prediction in complex networks has attracted increasing attention from
both physical and computer science communities. The algorithms can be used to
extract missing information, identify spurious interactions, evaluate network
evolving mechanisms, and so on. This article summaries recent progress about
link prediction algorithms, emphasizing on the contributions from physical
perspectives and approaches, such as the random-walk-based methods and the
maximum likelihood methods. We also introduce three typical applications:
reconstruction of networks, evaluation of network evolving mechanism and
classification of partially labelled networks. Finally, we introduce some
applications and outline future challenges of link prediction algorithms.Comment: 44 pages, 5 figure
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