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Showing papers by "Marco Furini published in 2015"


Journal ArticleDOI
TL;DR: Ass attitudes and behaviors of people toward a location-aware scenario are investigated; the amount of personal and sensitive data that can be extracted from contents publicly available in social platforms is shown; and users are asked for their opinions.
Abstract: The highavailability of geolocation technologies is changing the social media mobile scenario and is exposing users to privacy risks. Different studies have focused on location privacy in the mobile scenario, but the results are conflicting: some say that users are concerned about location privacy, others say they are not. In this paper, we initially investigate attitudes and behaviors of people toward a location-aware scenario; then, we show users the amount of personal and sensitive data that can be extracted from contents publicly available in social platforms, and finally we ask for their opinions about a location-aware scenario. Results show that people who were not initially concerned about privacy are the most worried about the location-aware scenario; conversely, people who were initially concerned are less worried about the location-aware scenario and find the scenario interesting. A deeper analysis of the obtained results allows us to draw guidelines that might be helpful to build an effective location-aware scenario.

55 citations


Proceedings ArticleDOI
16 Jul 2015
TL;DR: This paper proposes TRank, a novel method designed to address the problem of identifying the most influential Twitter users on specific topics identified with hashtags that combines different Twitter signals to provide three different indicators that are intended to capture different aspects of being influent.
Abstract: Twitter is the most popular real-time micro-blogging service and it is a platform where users provide and obtain information at rapid pace. In this scenario, one of the biggest challenge is to find a way to automatically identify the most influential users of a given topic. Currently, there are several approaches that try to address this challenge using different Twitter signals (e.g., number of followers, lists, metadata), but results are not clear and sometimes conflicting. In this paper, we propose TRank, a novel method designed to address the problem of identifying the most influential Twitter users on specific topics identified with hashtags. The novelty of our approach is that it combines different Twitter signals (that represent both the user and the user's tweets) to provide three different indicators that are intended to capture different aspects of being influent. The computation of these indicators is not based on the magnitude of the Twitter signals alone, but they are computed taking into consideration also human factors, as for example the fact that a user with many active followings might have a very noisy time lime and, thus, miss to read many tweets. The experimental assessment confirms that our approach provides results that are more reasonable than the one obtained by mechanisms based on the sole magnitude of data.

35 citations


Proceedings ArticleDOI
01 Jan 2015
TL;DR: ViMood is presented, a novel mechanism designed to improve the indexing of video material by integrating objective and subjective emotions and results obtained in the evaluation process showed that participants were very interested in the hybrid approach, as it fixes some of the problems of the objectives and subjective approaches.
Abstract: The use of emotions has recently been considered to improve the indexing of video contents and two different approaches are usually followed: computation of objective emotions through low-level video features analysis and computation of subjective emotions through analysis of the viewers' physical signals. In this paper, we propose a different approach and we present ViMood, a novel mechanism designed to improve the indexing of video material by integrating objective and subjective emotions. ViMood indexes every video scene with emotion(s) obtained through a combination of low-level feature analysis and on-the-fly viewer's emotion annotation. The goal is to allow viewers to browse video material using either general information (e.g., title, director) or specific emotions (e.g., “joy”, “sadness”, “surprise”). Results obtained in the evaluation process showed that participants were very interested in the hybrid approach, as it fixes some of the problems of the objective and subjective approaches.

5 citations


Book ChapterDOI
27 Oct 2015
TL;DR: It is observed that although the use of images in sentiment analysis can be useful to have insights about people sentiments, theUse of Instagram images may be slightly misleading.
Abstract: Understanding the sentiment of people is a process that may be useful when transforming a city into a smart city. A recent trend is to exploit social media data to infer people sentiments. While many studies focused on textual data, few considered the visual contents. In this paper we investigate whether the images available in the Instagram platform can be useful to understand people sentiments. Through an experimental assessment and two different validation methods, we observed that although the use of images in sentiment analysis can be useful to have insights about people sentiments, the use of Instagram images may be slightly misleading.

5 citations


Book ChapterDOI
27 Oct 2015
TL;DR: Results show that people would appreciate a tool able to help them connecting with food data and also show that current technologies are sufficient to create a food IoT scenario.
Abstract: People barely know what they eat and drink: product labels are written with small characters and with a difficult terminology. As a result, people spend too much time reading labels or avoid reading them at all. To connect food data with people we design of a food IoT (Internet of Things) scenario, where a smart cart tells us if the food product we are about to buy meet our preferences or not. In particular, we first perform a real-world study to understand consumers’ behavior while they shop; then we design a food IoT scenario and we use current technologies to investigate its feasibility. Results show that people would appreciate a tool able to help them connecting with food data and also show that current technologies are sufficient to create a food IoT scenario.

2 citations