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Concept

Blog

Résumé

Un blog, ou blogue, est un type de site web utilisé pour la publication périodique et régulière d'articles personnels, généralement succincts, rendant compte d'une actualité autour d'une thématique particulière. À la manière d'un journal intime, ces articles publiés par son/ses propriétaire(s) ou son/ses webmaster(s), sont généralement datés, signés et présentés dans un ordre rétrochronologique, c'est-à-dire du plus récent au plus ancien. Ils permettent à l'auteur, appelé blogueur, d’exprimer une opinion et sont la plupart du temps ouverts aux commentaires des lecteurs. , on dénombrait au moins de blogs et pas moins d'un million de nouveaux articles de blog publiés chaque jour. , de blogs aux États-Unis alors que dans le monde on estime à trois millions le nombre de blogs qui naissent chaque mois. Toutefois, le nombre de blogs inactifs demeure élevé. Rares sont en effet ceux qui affichent une grande longévité et la majorité d'entre eux sont abandonnés par les auteurs. Un blogue

Source officielle

https://fr.wikipedia.org/wiki/Blog

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This course is intended for students who want to understand modern large-scale data analysis systems and database systems. It covers a wide range of topics and technologies, and will prepare students to be able to build such systems as well as read and understand recent research publications.

In systems biology, proteomics represents an essential pillar. The understanding of protein function and regulation provides key information to decipher the complexity of living systems. Proteomic technology now enables deep quantitative proteome mapping via mass spectrometry.

This course provides an overview of information security and privacy topics. It introduces students to the knowledge and tools they will need to deal with the security/privacy challenges they are likely to encounter in today's Big Data world. The tools are illustrated with relevant applications.

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Four Banal

Romain Maxime Dubuis

«On appelle ce four villageois, un four banal. Banal est une lointaine référence au droit du moyen âge. “Ban” signifie “astreinte”. Le four banal était celui que le seigneur avait fait construire 1» pour les habitants de sa seigneurie et qui était disponible pour tous. Et si le four à pain traditionnel, (re)devenait un véritable catalyseur social, spatial, urbain et itinérant? Le projet met à disposition un foyer mobile qui, lorsqu’il s’installe dans un lieu, crée un sentiment de domesticité dans des contextes urbains qui ont bien souvent négligé l’échelle du quotidien et de l’individu, au profit de grands projets territoriaux. Le dispositif du four banal vient à nouveau donner un sens de communauté et requalifie l’urbain grâce à son foyer, centre de gravité autour duquel on se réunit, on cuisine, on mange, on partage… Ainsi, ce petit monument au pain (le mot panis, latin, a donné compagnon), part à la rescousse de la ville et de ses habitants. Farine, eau, sel. Pétrir, laisser lever, cuire. 1.http://reynaudrrcc.over-blog.com/article-le-four-banal-chez-nos-ancetres-definition-explication-69103634.html

2018

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Mining Conversational Social Video

Joan Isaac Biel Tres

The ubiquity of social media in our daily life, the intense user participation, and the explosion of multimedia content have generated an extraordinary interest from computer and social scientists to investigate the traces left by users to understand human behavior online. From this perspective, YouTube can be seen as the largest collection of audiovisual human behavioral data, among which conversational video blogs (vlogs) are one of the basic formats. Conversational vlogs have evolved from the initial "chat from your bedroom" format to a rich form of expression and communication that is expanding to innovative applications where a more natural and engaging way of reaching audiences is either necessary or might be beneficial. This video genre, available online in huge quantities, is a unique scenario for the study and characterization of complex human behavior in social media, that contrarily to social networks, text blogs, and microblogs, has remained unexplored so far. The automatic behavioral understanding of conversational vlogs is a new domain for multimedia research. In short, the goal of our research is the understanding of the processes involved in this social media type, based not only on the verbal channel – what is said – but also on the nonverbal channel – how it is said. The nonverbal channel includes prosody, gaze, facial expression, posture, gesture, etc. and has been studied in depth in the field of nonverbal communication. While the study of vlogging contributes to user behavior research in social media, it also adds to a larger research agenda in social computing by analyzing behavioral data at scales not previously achievable in other scenarios. These type of analysis pose important challenges regarding the development and integration of methods for robust and tractable audiovisual processing. In this thesis, we address the problem of mining user behavior inside conversational videos by addressing three main aspects. First, we integrate state-of-the art audio processing and computer vision techniques to analyze conversational social video. While the initial focus of the thesis is the nonverbal aspect of vlogger behavior, we also investigate the verbal content. Second, we study some of the interpersonal and social processes that link vlogger behavior and vlog consumption in social media platforms such as YouTube. In this context, we examine the phenomenon of social attention in vlogs, and we investigate the use of crowdsourcing as a scalable method to annotate large multimodal corpora with interpersonal perception impressions. Finally, we propose a computational framework to predict interpersonal impressions automatically using multimedia analysis, crowdsourced impressions, and machine learning techniques. We anticipate that the work presented in this dissertation will motivate future work in social and behavioral sciences, media analysis, natural language processing, and affective and social computing applied to the large-scale analysis of human interaction in social video.

EPFL2013

Chargement

The ubiquity of social media in our daily life, the intense user participation, and the explo- sion of multimedia content have generated an extraordinary interest from computer and social scientists to investigate the traces left by users to understand human behavior online. From this perspective, YouTube can be seen as the largest collection of audiovisual human behavioral data, among which conversational video blogs (vlogs) are one of the basic formats. Conversational vlogs have evolved from the initial "chat from your bedroom" format to a rich form of expression and communication that is expanding to innovative applications where a more natural and engaging way of reaching audiences is either necessary or might be beneficial. This video genre, available online in huge quantities, is a unique scenario for the study and characterization of complex human behavior in social media, that contrarily to social networks, text blogs, and microblogs, has remained unexplored so far. The automatic behavioral understanding of conversational vlogs is a new domain for multimedia research. In short, the goal of our research is the understanding of the processes involved in this social media type, based not only on the verbal channel – what is said – but also on the nonverbal channel – how it is said. The nonverbal channel includes prosody, gaze, facial expression, posture, gesture, etc. and has been studied in depth in the field of nonverbal communication. While the study of vlogging contributes to user behavior research in social media, it also adds to a larger research agenda in social computing by analyzing behavioral data at scales not previously achievable in other scenarios. These type of analysis pose important challenges regarding the development and integration of methods for robust and tractable audiovisual processing. In this thesis, we address the problem of mining user behavior inside conversational videos by addressing three main aspects. First, we integrate state-of-the art audio processing and computer vision techniques to analyze conversational social video. While the initial focus of the thesis is the nonverbal aspect of vlogger behavior, we also investigate the verbal content. Second, we study some of the interpersonal and social processes that link vlogger behavior and vlog consumption in social media platforms such as YouTube. In this context, we examine the phenomenon of social attention in vlogs, and we investigate the use of crowdsourcing as a scalable method to annotate large multimodal corpora with interpersonal perception impres- sions. Finally, we propose a computational framework to predict interpersonal impressions automatically using multimedia analysis, crowdsourced impressions, and machine learning techniques. We anticipate that the work presented in this dissertation will motivate future work in social and behavioral sciences, media analysis, natural language processing, and affective and social computing applied to the large-scale analysis of human interaction in social video.

EPFL2013

Chargement

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Mining Conversational Social Video

Joan Isaac Biel Tres

EPFL2013