54 research outputs found
Topology-aware indexing system for Urban Knowledge
Maps are being widely used as tools for presenting or retrieving information with spatial attributes. Existing map-based applications do not use the full potential of digital maps and geographical data: social media are disconnected from the underlying geographical entities; maps as visualization tools do not use the urban topology to cluster point of interest; maps as input systems are intrinsically ambiguous. This work presents a topology-aware indexing system supporting a new metaphor for a real integration between social media and digital maps. The methodology and technical solutions required to build and populate the indexing table starting from OpenStreetMap spatial primitives are introduced
Collaborative Multi-Perspective Urban Knowledge and Civic Media: A Never-Ending Design Challenge
Developing a civic social network requires to consider
users meeting in real life, collaborating on digital entries related
to real urban entities. This makes necessary to think about
collaboration tools in a new perspective: ensuring the
participation of users with different levels and forms of
legitimacy to represent complex relations among entities, and
ensuring the accountability of each contributor. We present a
set of technical solutions allowing the collaboration on complex
entities, keeping interactions simple, and representing multiple
perspectives about shared entities
Friendship prediction and homophily in social media
International audienceSocial media have attracted considerable attention because their open-ended nature allows users to create lightweight semantic scaffolding to organize and share content. To date, the interplay of the social and topical components of social media has been only partially explored. Here, we study the presence of homophily in three systems that combine tagging social media with online social networks. We find a substantial level of topical similarity among users who are close to each other in the social network. We introduce a null model that preserves user activity while removing local correlations, allowing us to disentangle the actual local similarity between users from statistical effects due to the assortative mixing of user activity and centrality in the social network. This analysis suggests that users with similar interests are more likely to be friends, and therefore topical similarity measures among users based solely on their annotation metadata should be predictive of social links. We test this hypothesis on several datasets, confirming that social networks constructed from topical similarity capture actual friendship accurately. When combined with topological features, topical similarity achieves a link prediction accuracy of about 92%
Niche as a determinant of word fate in online groups
Patterns of word use both reflect and influence a myriad of human activities
and interactions. Like other entities that are reproduced and evolve, words
rise or decline depending upon a complex interplay between {their intrinsic
properties and the environments in which they function}. Using Internet
discussion communities as model systems, we define the concept of a word niche
as the relationship between the word and the characteristic features of the
environments in which it is used. We develop a method to quantify two important
aspects of the size of the word niche: the range of individuals using the word
and the range of topics it is used to discuss. Controlling for word frequency,
we show that these aspects of the word niche are strong determinants of changes
in word frequency. Previous studies have already indicated that word frequency
itself is a correlate of word success at historical time scales. Our analysis
of changes in word frequencies over time reveals that the relative sizes of
word niches are far more important than word frequencies in the dynamics of the
entire vocabulary at shorter time scales, as the language adapts to new
concepts and social groupings. We also distinguish endogenous versus exogenous
factors as additional contributors to the fates of words, and demonstrate the
force of this distinction in the rise of novel words. Our results indicate that
short-term nonstationarity in word statistics is strongly driven by individual
proclivities, including inclinations to provide novel information and to
project a distinctive social identity.Comment: Supporting Information is available here:
http://www.plosone.org/article/fetchSingleRepresentation.action?uri=info:doi/10.1371/journal.pone.0019009.s00
Dynamics in online social networks
An increasing number of today's social interactions occurs using online
social media as communication channels. Some online social networks have become
extremely popular in the last decade. They differ among themselves in the
character of the service they provide to online users. For instance, Facebook
can be seen mainly as a platform for keeping in touch with close friends and
relatives, Twitter is used to propagate and receive news, LinkedIn facilitates
the maintenance of professional contacts, Flickr gathers amateurs and
professionals of photography, etc. Albeit different, all these online platforms
share an ingredient that pervades all their applications. There exists an
underlying social network that allows their users to keep in touch with each
other and helps to engage them in common activities or interactions leading to
a better fulfillment of the service's purposes. This is the reason why these
platforms share a good number of functionalities, e.g., personal communication
channels, broadcasted status updates, easy one-step information sharing, news
feeds exposing broadcasted content, etc. As a result, online social networks
are an interesting field to study an online social behavior that seems to be
generic among the different online services. Since at the bottom of these
services lays a network of declared relations and the basic interactions in
these platforms tend to be pairwise, a natural methodology for studying these
systems is provided by network science. In this chapter we describe some of the
results of research studies on the structure, dynamics and social activity in
online social networks. We present them in the interdisciplinary context of
network science, sociological studies and computer science.Comment: 17 pages, 4 figures, book chapte
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