Johnnatan Messias

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Search systems in online social media sites are frequently used to find information about ongoing events and people. For topics with multiple competing perspectives, such as political events or political candidates, bias in the top ranked results significantly shapes public opinion. However, bias does not emerge from an algorithm alone. It is important to(More)
Recently, there have been considerable efforts to use online data to investigate international migration. These efforts show that Web data are valuable for estimating migration rates and are relatively easy to obtain. However, existing studies have only investigated flows of people along migration corridors, i.e. between pairs of countries. In our work, we(More)
Users of social media sites like Facebook and Twitter rely on crowdsourced content recommendation systems (e.g., Trend-ing Topics) to retrieve important and useful information. Contents selected for recommendation indirectly give the initial users who promoted (by liking or posting) the content an opportunity to propagate their messages to a wider audience.(More)
Recently, there have been considerable efforts to use online data to investigate international migration. These efforts show that Web data are valuable for estimating migration rates and are relatively easy to obtain. However, existing studies have only investigated flows of people along migration corridors, i.e. between pairs of countries. In our work, we(More)
The increasing use of smartphones to access social media platforms opens a new wave of applications that explore sentiment analysis in the mobile environment. However, there are various existing sentiment analysis methods and it is unclear which of them are deployable in the mobile environment. This paper provides the first of a kind study in which we(More)
On most online social media sites today, user-generated data remains accessible to allowed viewers unless and until the data owner changes her privacy preferences. In this paper , we present a large-scale measurement study focussed on understanding how users control the longitudinal exposure of their publicly shared data on social media sites. Our study,(More)
Currently available data about people whose left their home country to live in a foreign country does not adequately capture the standards of contemporary global migration flows. A new trend for migration studies is to study the data from the Internet, either by Social Networks or other data in the WEB. In this study, we collected users data from the social(More)
Sarcasm and irony are widely used forms of speech used inside and outside the Web, having the power to transform a sentence regarding its polarity or sense. The ability of characterizing and detecting sarcastic and ironic messages on data collected from Web could improve many decision-making systems based on Natural Language Processing (NLP) such as the(More)