8,551 research outputs found
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
Context Aware Computing for The Internet of Things: A Survey
As we are moving towards the Internet of Things (IoT), the number of sensors
deployed around the world is growing at a rapid pace. Market research has shown
a significant growth of sensor deployments over the past decade and has
predicted a significant increment of the growth rate in the future. These
sensors continuously generate enormous amounts of data. However, in order to
add value to raw sensor data we need to understand it. Collection, modelling,
reasoning, and distribution of context in relation to sensor data plays
critical role in this challenge. Context-aware computing has proven to be
successful in understanding sensor data. In this paper, we survey context
awareness from an IoT perspective. We present the necessary background by
introducing the IoT paradigm and context-aware fundamentals at the beginning.
Then we provide an in-depth analysis of context life cycle. We evaluate a
subset of projects (50) which represent the majority of research and commercial
solutions proposed in the field of context-aware computing conducted over the
last decade (2001-2011) based on our own taxonomy. Finally, based on our
evaluation, we highlight the lessons to be learnt from the past and some
possible directions for future research. The survey addresses a broad range of
techniques, methods, models, functionalities, systems, applications, and
middleware solutions related to context awareness and IoT. Our goal is not only
to analyse, compare and consolidate past research work but also to appreciate
their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201
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