João Paulo Pesce

As the area of information visualization grows, a massive amount of visualization techniques has been developed. Consequently, the choice of an appropriate visualization has become more complex, usually resulting in unsatisfactory data analysis. Although there exist models and classifications that could guide the choice of a visualization technique, they are mostly generalist and do not present a clear methodology for evaluation and evolution. In contrast, we propose an annotation process for… Mostrar más

As the area of information visualization grows, a massive amount of visualization techniques has been developed. Consequently, the choice of an appropriate visualization has become more complex, usually resulting in unsatisfactory data analysis. Although there exist models and classifications that could guide the choice of a visualization technique, they are mostly generalist and do not present a clear methodology for evaluation and evolution. In contrast, we propose an annotation process for data visualization techniques based on an initial capability-driven collection of and concepts that encomes visual components of both well established as well as modern visualization techniques. To demonstrate the initial collections expressiveness, we present a qualitative analysis of an experiment with specialist s at annotating visualization techniques from the D3 (Data-Driven Documents) library. Furthermore, to show the completeness of the collection, we automatically assess its coverage of all published papers from six major international information visualization conferences since 1995. Our results attest the expressiveness of the initial collection and its coverage of over 99% of the analysed literature. Finally, we discuss the limitations and alternatives for semi-automatically evolving the annotation process as new visualization techniques are developed and how the spread of this type of methodology could benefit the information visualization community. Mostrar menos

To increase mobile engagement, photo sharing sites are trying to identify interesting and memorable pictures. Past proposals for identifying such pictures have relied on either metadata (e.g., likes) or visual features. In practice, techniques based on those two inputs do not always work: meta- data is sparse (only few pictures have considerable number of likes), and extracting visual features is computationally ex- pensive. In mobile solutions, geo-referenced content becomes increasingly… Mostrar más

To increase mobile engagement, photo sharing sites are trying to identify interesting and memorable pictures. Past proposals for identifying such pictures have relied on either metadata (e.g., likes) or visual features. In practice, techniques based on those two inputs do not always work: meta- data is sparse (only few pictures have considerable number of likes), and extracting visual features is computationally ex- pensive. In mobile solutions, geo-referenced content becomes increasingly important. The premise behind this work is that pictures of a neighbourhood are related to the way the neighbourhood is perceived by people: whether it is, for instance, distinctive and beautiful or not. Since 1970s, urban theories proposed by Lynch, Milgram and Peterson aimed at systematically capturing the way people perceive neighbourhoods. Here we tested whether those theories could be put to use for automatically identifying appealing city pictures. We did so by gathering geo-referenced Flickr pictures in the city of Lon- don; selecting six urban qualities associated with those urban theories; computing proxies for those qualities from online social media data; and ranking Flickr pictures based on those proxies. We find that our proposal enjoys three main desirable properties: it is effective, scalable, and aware of contextual changes such as time of day and weather condition. All this suggests new promising research directions for multi-modal learning approaches that automatically identify appealing city pictures. Mostrar menos

Today, it is the norm for online social (OSN) s to have s on multiple services. For example, a recent study showed that 34% of all Twitter s also use Pinterest. This situation leads to interesting questions such as: Are the activities that s perform on each site dist? Alternatively, if s perform the same actions on multiple sites, where does the information originate? Given the interlinking between social networks, failure to understand activity across multiple sites… Mostrar más

Today, it is the norm for online social (OSN) s to have s on multiple services. For example, a recent study showed that 34% of all Twitter s also use Pinterest. This situation leads to interesting questions such as: Are the activities that s perform on each site dist? Alternatively, if s perform the same actions on multiple sites, where does the information originate? Given the interlinking between social networks, failure to understand activity across multiple sites may obfuscate the true information dissemination dynamics of the social web.
In this study, we take the first steps towards a more complete understanding of behaviour across multiple OSNs. We collect a sample of over 30,000 s that have s on both Twitter and Pinterest, crawling their profile information and activity on a daily basis for a period of almost three months. We develop a novel methodology for comparing activity across these two sites. We find that the global patterns of use across the two sites differ significantly, and that s tend to post items to Pinterest before posting them on Twitter. Our findings can inform the understanding of the behaviour of s on individual sites, as well as the dynamics of sharing across the social web. Mostrar menos

Online social networks (OSNs) have become popular platforms for people to connect and interact with each other. Among those networks, Pinterest has recently become noteworthy for its growth and promotion of visual over textual content. The purpose of this study is to analyze this image-based network in a gender-sensitive fashion, in order to understand (i) motivation and usage pattern in the network, (ii) how communications and social interactions happen and (iii) how s describe… Mostrar más

Online social networks (OSNs) have become popular platforms for people to connect and interact with each other. Among those networks, Pinterest has recently become noteworthy for its growth and promotion of visual over textual content. The purpose of this study is to analyze this image-based network in a gender-sensitive fashion, in order to understand (i) motivation and usage pattern in the network, (ii) how communications and social interactions happen and (iii) how s describe themselves to others. This work is based on more than 220 million items generated by 683,273 s. We were able to find significant differences w.r.t. all mentioned aspects. We observed that, although the network does not encourage direct social communication, females make more use of lightweight interactions than males. Moreover, females invest more effort in reciprocating social links, are more active and generalist in content generation, and describe themselves using words of affection and positive emotions. Males, on the other hand, are more likely to be specialists and tend to describe themselves in an assertive way. We also observed that each gender has different interests in the network, females tend to make more use of the network’s commercial capabilities, while males are more prone to the role of curators of items that reflect their personal taste. It is important to understand gender differences in online social networks, so one can design services and applications that leverage human social interactions and provide more targeted and relevant experiences. Mostrar menos

Planners and social psychologists have suggested that the recognizability of the urban environment is linked to people's socio-economic well-being. We build a web game that puts the recognizability of London's streets to the test. It follows as closely as possible one experiment done by Stanley Milgram in 1972. The game picks up random locations from Google Street View and tests s to see if they can judge the location in of closest subway station, borough, or region. Each participant… Mostrar más

Planners and social psychologists have suggested that the recognizability of the urban environment is linked to people's socio-economic well-being. We build a web game that puts the recognizability of London's streets to the test. It follows as closely as possible one experiment done by Stanley Milgram in 1972. The game picks up random locations from Google Street View and tests s to see if they can judge the location in of closest subway station, borough, or region. Each participant dedicates only few minutes to the task (as opposed to 90 minutes in Milgram's). We collect data from 2,255 participants (one order of magnitude a larger sample) and build a recognizability map of London based on their responses. We find that some boroughs have little cognitive representation; that recognizability of an area is explained partly by its exposure to Flickr and Foursquare s and mostly by its exposure to subway engers; and that areas with low recognizability do not fare any worse on the economic indicators of income, education, and employment, but they do signi cantly su er from social problems of housing deprivation, poor living conditions, and crime. These results could not have been produced without analyzing life o - and online: that is, without considering the interactions between urban places in the physical world and their virtual presence on platforms such as Flickr and Foursquare. This line of work is at the crossroad of two emerging themes in computing research - a crossroad where "web science" meets the "smart city" agenda. Mostrar menos

Social media profiles are telling examples of the everyday need for disclosure and concealment. The balance between concealment and disclosure varies across individuals, and personality traits might partly explain this variability. Experimental findings on the relationship between information disclosure and personality have been so far inconsistent. We thus study this relationship anew with 1,313 Facebook s in the United States using two personality tests: the big five personality test and the… Mostrar más

Social media profiles are telling examples of the everyday need for disclosure and concealment. The balance between concealment and disclosure varies across individuals, and personality traits might partly explain this variability. Experimental findings on the relationship between information disclosure and personality have been so far inconsistent. We thus study this relationship anew with 1,313 Facebook s in the United States using two personality tests: the big five personality test and the self-monitoring test. We model the process of information disclosure in a principled way using Item Response Theory and correlate the resulting disclosure scores with personality traits. We find a correlation with the trait of Openness and observe gender effects, in that, men and women share equal amount of private information, but men tend to make it more publicly available, well beyond their social circles. Interestingly, geographic (e.g., residence, hometown) and work-related information is used as relationship currency, in that, it is selectively shared with social s and is rarely shared with the Facebook community at large. Mostrar menos

Social-networking s unknowingly reveal certain kinds of personal information that malicious attackers could profit from to perpetrate significant privacy breaches. This paper quantitatively demonstrates how the simple act of tagging pictures on the social-networking site of Facebook could reveal private attributes that are extremely sensitive. Our results suggest that photo tags can be used to help predicting some, but not all, of the analyzed attributes. We believe our analysis make… Mostrar más

Social-networking s unknowingly reveal certain kinds of personal information that malicious attackers could profit from to perpetrate significant privacy breaches. This paper quantitatively demonstrates how the simple act of tagging pictures on the social-networking site of Facebook could reveal private attributes that are extremely sensitive. Our results suggest that photo tags can be used to help predicting some, but not all, of the analyzed attributes. We believe our analysis make s aware of significant breaches of their privacy and could inform the design of new privacy-preserving ways of tagging pictures on social-networking sites. Mostrar menos