208 research outputs found
The Shortest Path to Happiness: Recommending Beautiful, Quiet, and Happy Routes in the City
When providing directions to a place, web and mobile mapping services are all
able to suggest the shortest route. The goal of this work is to automatically
suggest routes that are not only short but also emotionally pleasant. To
quantify the extent to which urban locations are pleasant, we use data from a
crowd-sourcing platform that shows two street scenes in London (out of
hundreds), and a user votes on which one looks more beautiful, quiet, and
happy. We consider votes from more than 3.3K individuals and translate them
into quantitative measures of location perceptions. We arrange those locations
into a graph upon which we learn pleasant routes. Based on a quantitative
validation, we find that, compared to the shortest routes, the recommended ones
add just a few extra walking minutes and are indeed perceived to be more
beautiful, quiet, and happy. To test the generality of our approach, we
consider Flickr metadata of more than 3.7M pictures in London and 1.3M in
Boston, compute proxies for the crowdsourced beauty dimension (the one for
which we have collected the most votes), and evaluate those proxies with 30
participants in London and 54 in Boston. These participants have not only rated
our recommendations but have also carefully motivated their choices, providing
insights for future work.Comment: 11 pages, 7 figures, Proceedings of ACM Hypertext 201
The Emotional and Chromatic Layers of Urban Smells
People are able to detect up to 1 trillion odors. Yet, city planning is
concerned only with a few bad odors, mainly because odors are currently
captured only through complaints made by urban dwellers. To capture both good
and bad odors, we resort to a methodology that has been recently proposed and
relies on tagging information of geo-referenced pictures. In doing so for the
cities of London and Barcelona, this work makes three new contributions. We
study 1) how the urban smellscape changes in time and space; 2) which emotions
people share at places with specific smells; and 3) what is the color of a
smell, if it exists. Without social media data, insights about those three
aspects have been difficult to produce in the past, further delaying the
creation of urban restorative experiences.Comment: 11 pages, 18 figures, final version published in the Proceedings of
the Tenth International Conference on Web and Social Media (ICWSM 2016
Smelly Maps: The Digital Life of Urban Smellscapes
Smell has a huge influence over how we perceive places. Despite its
importance, smell has been crucially overlooked by urban planners and
scientists alike, not least because it is difficult to record and analyze at
scale. One of the authors of this paper has ventured out in the urban world and
conducted smellwalks in a variety of cities: participants were exposed to a
range of different smellscapes and asked to record their experiences. As a
result, smell-related words have been collected and classified, creating the
first dictionary for urban smell. Here we explore the possibility of using
social media data to reliably map the smells of entire cities. To this end, for
both Barcelona and London, we collect geo-referenced picture tags from Flickr
and Instagram, and geo-referenced tweets from Twitter. We match those tags and
tweets with the words in the smell dictionary. We find that smell-related words
are best classified in ten categories. We also find that specific categories
(e.g., industry, transport, cleaning) correlate with governmental air quality
indicators, adding validity to our study.Comment: 11 pages, 7 figures, Proceedings of 9th International AAAI Conference
on Web and Social Media (ICWSM2015
The Social World of Content Abusers in Community Question Answering
Community-based question answering platforms can be rich sources of
information on a variety of specialized topics, from finance to cooking. The
usefulness of such platforms depends heavily on user contributions (questions
and answers), but also on respecting the community rules. As a crowd-sourced
service, such platforms rely on their users for monitoring and flagging content
that violates community rules.
Common wisdom is to eliminate the users who receive many flags. Our analysis
of a year of traces from a mature Q&A site shows that the number of flags does
not tell the full story: on one hand, users with many flags may still
contribute positively to the community. On the other hand, users who never get
flagged are found to violate community rules and get their accounts suspended.
This analysis, however, also shows that abusive users are betrayed by their
network properties: we find strong evidence of homophilous behavior and use
this finding to detect abusive users who go under the community radar. Based on
our empirical observations, we build a classifier that is able to detect
abusive users with an accuracy as high as 83%.Comment: Published in the proceedings of the 24th International World Wide Web
Conference (WWW 2015
Journal of Internet Services and Applications manuscript No. (will be inserted by the editor) Middleware for Social Computing: A
Abstract Social computing broadly refers to supporting social behaviours using computational systems. In the last decade, the advent of Web 2.0 and its social networking services, wikis, blogs, and social bookmarking has revolutionised social computing, creating new online contexts within which people interact socially (social networking). With the pervasiveness of mobile devices and embedded sensors, we stand at the brink of another major revolution, where the boundary between online and offline social behaviours blurs, providing opportunities for (re)defining social conventions and contexts once again. But opportunities come with challenges: can middleware foster the engineering of social software? We identify three societal grand challenges that are likely to drive future research in social computing and elaborate on how the middleware community can help address them
Cultures in Community Question Answering
CQA services are collaborative platforms where users ask and answer
questions. We investigate the influence of national culture on people's online
questioning and answering behavior. For this, we analyzed a sample of 200
thousand users in Yahoo Answers from 67 countries. We measure empirically a set
of cultural metrics defined in Geert Hofstede's cultural dimensions and Robert
Levine's Pace of Life and show that behavioral cultural differences exist in
community question answering platforms. We find that national cultures differ
in Yahoo Answers along a number of dimensions such as temporal predictability
of activities, contribution-related behavioral patterns, privacy concerns, and
power inequality.Comment: Published in the proceedings of the 26th ACM Conference on Hypertext
and Social Media (HT'15
Cooperation in small groups: the effect of group size
We study the effect of group size on cooperation in voluntary contribution mechanism games. As in previous experiments, we study four- and eight-person groups in high and low marginal per capita return (MPCR) conditions. We find a positive effect of group size in the low MPCR condition, as in previous experiments. However, in the high MPCR condition we observe a negative group size effect. We extend the design to investigate two- and three-person groups in the high MPCR condition, and find that cooperation is highest of all in two-person groups. The findings in the high MPCR condition are consistent with those from n-person prisoner’s dilemma and oligopoly experiments that suggest it is more difficult to sustain cooperation in larger groups. The findings from the low MPCR condition suggest that this effect can be overridden. In particular, when cooperation is low other factors, such as considerations of the social benefits of contributing (which increase with group size), may dominate any negative group size effect
Multidimensional Tie Strength and Economic Development
The strength of social relations has been shown to affect an individual’s access to opportunities. To date, however, the correspondence between tie strength and population’s economic prospects has not been quantified, largely because of the inability to operationalise strength based on Granovetter’s classic theory. Our work departed from the premise that tie strength is a unidimensional construct (typically operationalized with frequency or volume of contact), and used instead a validated model of ten fundamental dimensions of social relationships grounded in the literature of social psychology. We built state-of-the-art NLP tools to infer the presence of these dimensions from textual communication, and analyzed a large conversation network of 630K geo-referenced Reddit users across the entire US connected by 12.8M social ties created over the span of 7 years. We found that unidimensional tie strength is only weakly correlated with economic opportunities ([Formula: see text] ), while multidimensional constructs are highly correlated ([Formula: see text] ). In particular, economic opportunities are associated to the combination of: (i) knowledge ties, which bridge geographically distant groups, facilitating the knowledge dissemination across communities; and (ii) social support ties, which knit geographically close communities together, and represent dependable sources of social and emotional support. These results point to the importance of developing high-quality measures of tie strength in network theory
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