除了文字訊息，張貼相片也是臉書使用者常用的功能，這些上傳的照片種類繁多，可能是自拍照、風景照、或食物照等等，本論文的研究以影像分析為出發點，探討相片內容跟發佈者間之關係，希望藉由相片獲得的資訊，輔助分析使用者樣貌。 本研究共收集32位受測者上傳至臉書的相片，利用電腦視覺技術分析圖像內容，如人臉偵測、環境識別、找出影像上視覺顯著的區域等，藉由這些工具所提供的資訊，將照片加註標籤，以及進行自動分類，並以此兩個層次的資訊做為特徵向量，利用階層式演算法進行使用者分群，再根據實驗結果去分析每一群的行為特性。 透過此研究，可對使用者進行初步分類、瞭解不同的使用者樣貌，並嘗試回應相關問題，如使用者所張貼之相片種類統計、不同性別使用者的上傳行為、 依據上傳圖像內容，進行使用者樣貌分類等，深化我們對於臉書相片上傳行為的理解。 / Apart from text messages, photo posting is a popular function of Facebook. The uploaded photos are of various nature, including selfie, outdoor scenes, and food. In this thesis, we employ state-of-the-art computer vision techniques to analyze image content and establish the relationship between user profile and the type of photos posted. We collected photos from 32 Facebook users. We then applied techniques such as face detection, scene understanding and saliency map identification to gather information for automatic image tagging and classification. Grouping of users can be achieved either by tag statistics or photo classes. Characteristics of each group can be further investigated based on the results of hierarchical clustering. We wish to identify profiles of different users and respond to questions such as the type of photos most frequently posted, gender differentiation in photo posting behavior and user classification according to image content, which will promote our understanding of photo uploading activities on Facebook.

Trotz substantieller ökonomischer und sozialer Implikationen des World Wide Webs existiert noch immer eine überraschend große Forschungslücke in Bezug auf empirische Untersuchungen der Webnutzung. Insbesondere bezüglich der individuellen Webnutzung weiß man heute noch wenig über Schlüsselthemen dieses Forschungsfeldes, wie zum Beispiel die Anzahl der Webseitenbesuche von Individuen, der Loyalität von Nutzern, und den demographischen Charakteristika, die bestimmend für die Internetnutzung sind. Deshalb sieht sich diese Dissertation als Schritt zur Überbrückung dieser Forschungslücke. Sie präsentiert die gewonnenen Erkenntnisse verschiedener, voneinander abhängiger, empirischer Studien der individuellen Webnutzung Pittsburgher Bürger. Diese Dissertation erweitert die Forschung im Bereich individuellen Webnutzungsverhaltens durch: - die Analyse des Einflusses der steigenden Anzahl von Webangeboten auf die individuelle Webnutzung, - die anwendung sessionbasierter Maße auf individuelle Webnutzungsdaten, um Einsichten in den Verlauf der Webnutzung bei gleichzeitigem Anstieg der individuellen Weberfahrung zu erhalten, - die Analyse der Loyalitaet im Web von einzelnen Nutzergruppen, um die Frage zu beantworten, ob Nutzergruppen zu favorisierten Seiten im Web konvergieren, - spezifisches Herangehen an das Thema der Portalnutzung im Web und das Beantworten der Frage, ob sich Portalnutzer von durchschnittlichen Internetnutzern unterscheiden. Aus betriebswirtschaftlicher und volkswirtschaftlicher Sicht interessante Webnutzungsmaße werden entwickelt und diskutiert. Die Anwendung dieser Maße führt zu Erkenntnissen bezüglich signifikanter Trends. So wird beispielsweise deutlich, dass keinesfalls eine Gleichverteilung der Nutzung über Nutzer und Zeit besteht. Nutzer können in vier Gruppen mit verschiedenen Entwicklungskurven eingeteilt werden. Alle Nutzergruppen nähern sich über die Zeit Sättigungsgrenzen der Webnutzung an. Außerdem verbringen die meisten Nutzer nur wenig Zeit im Internet. Auch wird deutlich dass Loyalität im Web äußerst gering ist und Webnutzer trotz steigender Erfahrung im Umgang mit dem Internet nicht sonderlich gezieltes Surfverhalten entwickeln. Zusätzlich führt die Anwendung von Regressionsmodellen zu Erkenntnissen über die individuellen Charakteristika, welche die Webnutzung beeinflussen. Solch Charakteristika sind zum Beispiel ethnische Herkunft, Geschlecht, Haushaltseinkommen, Telefon- und Emailnutzung und Computerkenntnisse. Daher liefert die vorliegende Arbeit Erkenntnisse, welche sowohl aus betriebswirtschaftlicher Sicht als auch aus volkswirtschaftlicher Sicht Relevanz haben. Insbesondere können Marketingabteilungen, vor allem in der Informations- und Kommunikationsindustrie, von den vorliegen Resultaten profitieren. Themen wie Webloyalität und Webnutzung, die in der vorliegenden Arbeit angesprochen werden, sind insbesondere relevant für Geschäftsmodelle aus dem B2C Bereich. Adressaten sind dementsprechend zum Beispiel Internetfirmen, welche von Werbeeinkünften aus Bannerwerbung abhängig sind und Firmen, welche einen hohen Grad an Loyalität unter Ihren Webnutzern suchen. Außerdem bilden die Erkenntnisse die Grundlage für staatliche Initiativen, die der Sicherstellung des Zugangs zum Internet alle Gruppen der Bevölkerung dienen. Die vorliegende Arbeit reichert die empirische Grundlage, welche zum Verständnis individueller Webnutzung nötig ist, an. Die Erkenntnisse sind insbesondere für am neuen Informationszeitalter teilhabenden Individuen und Institutionen, auch staatlicher Art, interessant. / Despite the substantial social and economic implications of the World Wide Web, there is still a surprising lack of empirical research on Web usage. Specifically, at the level of the individual user, little is known about key issues of Internet usage, such as the trajectory of change over time in the number of visits to Web sites, the degree of individual loyalty to Web sites, and the demographics that determine Web usage. In order to overcome this lack of research, we report in this dissertation the results of several interrelated studies of individual Web usage patterns of average citizens from the Pittsburgh area. This dissertation advances the research on individual Web usage by: - analyzing the impact of increasing Web site visiting opportunities on Web utilization rates of individual users, - employing session-based measures to data on individual Web usage in order to identify how Web users change the way they use the Web as their level of expertise increases, - analyzing whether different user groups also differ in loyalty to Web sites and whether users converge over time to a set of favorite Web sites, - specifically dealing with the issue of Web portal utilization to answer the question whether Web portal users are different from average Web users. We develop measures of Web usage that are particularly relevant from a business and public policy perspective. By applying these measures to longitudinal data on Web usage, we identify significant trends in individual Internet usage. For example, we reveal that individual Web usage is not distributed equally across subgroups of users. Web users can be clustered into four groups with distinct trajectories of Web usage. All groups reach saturation in their extent of Web usage after following a downward path. Further, most Web users spent only limited time in the Web and only a small group of users uses the Web heavily. Also, users show consistently little loyalty to Web sites. Surprisingly, as Web users gain experience in using the Web, there does not seem to be a significant shift from undirected browsing to directed access of Web sites over time. We apply regression models in order to predict the determinants of Web utilization. Individual characteristics, such as ethnic background, gender, household income, phone usage, e-mail usage, and computer skill level, determine Web usage. Thus, the results have implications for both electronic commerce and public policy as it pertains to the digital divide. They are particularly useful for marketing departments, especially in the information and communication industry. Discussions of Web user loyalty and Web visiting opportunities as conducted in this dissertation are relevant to business models in use in business-to-consumer electronic commerce, especially for Internet companies that rely on advertising income generated from serving banner advertisements and companies that need to maintain a high degree of customer loyalty. The results also provide the factual foundation for key policy initiatives to promote access to the Internet for all groups of people. Policy makers need data on Internet usage in order to measure the size of a possible digital divide and ensure that everybody belonging to the present and the next generation - and not a subgroup of people only - has access to the Internet. In summary, this study advances the empirical foundation for understanding individual Web use. The findings of this dissertation will be useful to stakeholders in the new Information Age, in particular marketing departments and policy makers.

企業越來越意識到使用者的重要性，知道產品設計必須以使用者為中心。但面對網路興起、讀者大量流失的報紙新聞媒體，該如何從使用者察覺出商業模式創新的機會，是當前文獻亟欲探索的主題。本論文因此提出兩大分析重點。第一，分析使用者的行為脈絡，由早期大眾的角色中找出使用者對資訊需求，理解創新擴散的關鍵。第二，透過使用者行為分析形成商業模式的各種可能性，了解如何能改變商業營運邏輯。本文以聯合報系旗下之《Upaper》捷運報做為個案，分析捷運族的移動行為與資訊需求，藉此鎖定十個新聞主題來分析使用者行為、資訊需求、設計洞見、設計方案等環環相扣的四個步驟。本研究歸納出三種人物誌：需要優先性資訊的懶人、喜愛連貫性資訊的達人、偏好比較性資訊的商人。這三種人物誌指引出三種可能的新商業模式：從新聞到情報、從廣告到商研、從紙媒到串媒。學理上，本研究提出使用者導向商業模式的形成過程及創新原則。實務上，新聞媒體組織可以理解分析使用者的微觀行為的步驟及策略。 / Enterprises are increasingly aware of the importance of users and know their product design must be user-centered. Now newspaper media is losing their readers due to the rising of Internet, so how to develop an innovative business model from users became one of hot topic of literature review. This thesis could be divided into two parts. Firstly, analyze the user behavior context in order to identify the information needs from the role of the early majority, and to realize the key point of innovation diffusion. Secondly, find the possibilities of business models through the user behavior analysis and learn how to change the business logic. In this paper, we use the United Daily News Group's "Upaper" as a case study of the mobile behavior and information needs of the commuters, thereby focusing the top ten news topics to analyze user behavior, information needs, design insights, design plan, these four steps which is closely connected and inseparable. This study identifies three Personas: lazy people who need priority information, Maven who like coherent information, businessman who prefer comparative information. These three personas point out three possible new business models: from news to intelligence, from advertising to business research, from newspaper media to the transmedia. Academically, this study presents the formation process and the innovative principles of the user-oriented business model. In practice, the media organization can understand the steps and strategies about how to analyze the user microscopic behavior.

The mission of the research presented in this thesis is to give computers the power to sense and react to human activities. Without the ability to sense the surroundings and understand what humans are doing, computers will not be able to provide active, timely, appropriate, and considerate services to the humans. To accomplish this mission, the work stands on the shoulders of two giants: Machine learning and ubiquitous computing. Because of the ubiquity of sensor-enabled mobile and wearable devices, there has been an emerging opportunity to sense, learn, and infer human activities from the sensor data by leveraging state-of-the-art machine learning algorithms. While having shown promising results in human activity recognition, most existing approaches using supervised or semi-supervised learning have two fundamental problems. Firstly, most existing approaches require a large set of labeled sensor data for every target class, which requires a costly effort from human annotators. Secondly, an unseen new activity cannot be recognized if no training samples of that activity are available in the dataset. In light of these problems, a new approach in this area is proposed in our research. This thesis presents our novel approach to address the problem of human activity recognition when few or no training samples of the target activities are available. The main hypothesis is that the problem can be solved by the proposed NuActiv activity recognition framework, which consists of modeling the hierarchical and sequential structure of human activities, as well as bringing humans in the loop of model training. By injecting human knowledge about the hierarchical nature of human activities, a semantic attribute representation and a two-layer attribute-based learning approach are designed. To model the sequential structure, a probabilistic graphical model is further proposed to take into account the temporal dependency of activities and attributes. Finally, an active learning algorithm is developed to reinforce the recognition accuracy using minimal user feedback. The hypothesis and approaches presented in this thesis are validated by two case studies and real-world experiments on exercise activities and daily life activities. Experimental results show that the NuActiv framework can effectively recognize unseen new activities even without any training data, with up to 70-80% precision and recall rate. It also outperforms supervised learning with limited labeled data for the new classes. The results significantly advance the state of the art in human activity recognition, and represent a promising step towards bridging the gap between computers and humans.

科技的演進可能改變了人們的生活行為。隨著智慧型手機的快速成長，數位敘事將會以一種嶄新的方式產出行動內容。我們透過互動設計的元素以及「行動敘事」的特性為依據，設計了一個無所不在的「行動協作數位敘事平台」，以促進這個改變能實現。利用這個平台，使用者根據他/她的所在地，不僅可以下載閱聽附近的行動內容，並且可以增修或記錄周遭的事物後上傳。我們並加進「協作」的功能到此平台，以提昇內容的多元與豐富，使得閱聽者，更能夠沉浸在敘述的內容當中。除此之外，本平台也增進網路技術，使其可以在離線時仍然可以持續記錄與協作內容，不受時空限制。 我們建置了這個平台以APP的型式在Android系統上呈現，並作田野實驗，以研究此新的行動協作敘事型態。我們針對平台進行兩個部分的評估與分析，其一為使用者介面的評估，我們以放聲思考法進行，並隨後對介面做出修正；其二為平台系統使用評估，此部分以訪談法進行，並同時與系統Log作比對驗證。平台實驗發現的設計元素以及使用行為，希望可以在未來對此領域欲進一步研究者，提供很好的建議。 / Technologies could change users’ behaviors. As the recent growth of mobile smartphones, digital narrative would have a new way to create mobile content. Through interactive design components and features of “mobile narrative”, we design a "Mobile Collaboration Digital Narrative Platform" to facilitate this change. A user can retrieve nearby mobile content, and also have the ability to add, edit or record what is happening at his/her present location. By adding the feature of “collaborative content creation” to the platform, the content can be made more diverse and rich and the reader can better immerse him or herself in it. Moreover, by the enhanced network technology, the platform can also work in offline mode to make it function ubiquitously. In order to study the new type of mobile collaborative narration, we develop the system (an Android App) and do field trial. We evaluate and analyze the system for two parts: one for the assessment of the user interface, and the other for system usage evaluation. We use the think aloud method for the former to amend interface design. For the latter, we interview with users, which are also compared with the system log for justification. The design components and the results for usage behaviors that we found from the new platform will provide a good recommendation for future further study in the field.

Durant les situations de crise, telles que les catastrophes, le besoin de recherche d’informations (RI) pertinentes partagées dans les microblogs en temps réel est inévitable. Cependant, le grand volume et la variété des flux d’informations partagées en temps réel dans de telles situations compliquent cette tâche. Contrairement aux approches existantes de RI basées sur l’analyse du contenu, nous proposons de nous attaquer à ce problème en nous basant sur les approches centrées utilisateurs tout en levant un certain nombre de verrous méthodologiques et technologiques inhérents : 1) à la collection des données partagées par les utilisateurs à évaluer, 2) à la modélisation de leurs comportements, 3) à l’analyse des comportements, et 4) à la prédiction et le suivi des utilisateurs primordiaux en temps réel. Dans ce contexte, nous détaillons les approches proposées dans cette thèse afin de prédire les utilisateurs primordiaux qui sont susceptibles de partager les informations pertinentes et exclusives ciblées et de permettre aux intervenants d’urgence d’accéder aux informations requises quel que soit le format (i.e. texte, image, vidéo, lien hypertexte) et en temps réel. Ces approches sont centrées sur trois principaux aspects. Nous avons tout d’abord étudié l’efficacité de différentes catégories de mesures issues de la littérature et proposées dans cette thèse pour représenter le comportement des utilisateurs. En nous basant sur les mesures pertinentes résultant de cette étude, nous concevons des nouvelles caractéristiques permettant de mettre en évidence la qualité des informations partagées par les utilisateurs selon leurs comportements. Le deuxième aspect consiste à proposer une approche de modélisation du comportement de chaque utilisateur en nous basant sur les critères suivants : 1) la modélisation des utilisateurs selon l’évolution de l’évènement, 2) la modélisation de l’évolution des activités des utilisateurs au fil du temps à travers une représentation sensible au temps, 3) la sélection des caractéristiques les plus discriminantes pour chaque phase de l’évènement. En se basant sur cette approche de modélisation, nous entraînons différents modèles de prédiction qui apprennent à différencier les comportements des utilisateurs primordiaux de ceux qui ne le sont pas durant les situations de crise. Les algorithmes SVM et MOG-HMMs ont été utilisés durant la phase d’apprentissage. La pertinence et l’efficacité des modèles de prédiction appris ont été validées à l’aide des données collectées par notre système multi-agents MASIR durant deux inondations qui ont eu lieu en France et des vérités terrain appropriées à ces collections. / During crisis events such as disasters, the need of real-time information retrieval (IR) from microblogs remains inevitable. However, the huge amount and the variety of the shared information in real time during such events over-complicate this task. Unlike existing IR approaches based on content analysis, we propose to tackle this problem by using user-centricIR approaches with solving the wide spectrum of methodological and technological barriers inherent to : 1) the collection of the evaluated users data, 2) the modeling of user behavior, 3) the analysis of user behavior, and 4) the prediction and tracking of prominent users in real time. In this context, we detail the different proposed approaches in this dissertation leading to the prediction of prominent users who are susceptible to share the targeted relevant and exclusive information on one hand and enabling emergency responders to have a real-time access to the required information in all formats (i.e. text, image, video, links) on the other hand. These approaches focus on three key aspects of prominent users identification. Firstly, we have studied the efficiency of state-of-the-art and new proposed raw features for characterizing user behavior during crisis events. Based on the selected features, we have designed several engineered features qualifying user activities by considering both their on-topic and off-topic shared information. Secondly, we have proposed a phase-aware user modeling approach taking into account the user behavior change according to the event evolution over time. This user modeling approach comprises the following new novel aspects (1) Modeling microblog users behavior evolution by considering the different event phases (2) Characterizing users activity over time through a temporal sequence representation (3) Time-series-based selection of the most discriminative features characterizing users at each event phase. Thirdly, based on this proposed user modeling approach, we train various prediction models to learn to differentiate between prominent and non-prominent users behavior during crisis event. The learning task has been performed using SVM and MoG-HMMs supervised machine learning algorithms. The efficiency and efficacy of these prediction models have been validated thanks to the data collections extracted by our multi-agents system MASIR during two flooding events who have occured in France and the different ground-truths related to these collections.

Idag kommer fler och fler i kontakt med nya digitala tekniker både inom yrket men även privat. Det är därför viktigare än någonsin att de digitala verktygen når upp till slutanvändares förväntningar såväl som krav. Syftet med denna studien var att undersöka fenomenet digital acceptans. Därför valdes modeller och teorier för utvärdering ut för att jämföras mot individens upplevelser och acceptans av digitala verktyg. En teoretisk grund har lagts genom att samla in och analysera nio modeller för utvärdering av system och användaracceptans, där tre modeller valdes ut. Studien har genomförts med hjälp av intervjuer där respondenter från olika yrkesbakgrunder har fått möjligheten att berätta om sina upplevelser kring digitaliseringen. Materialet från dessa intervjuer har därefter analyserats för att kategoriseras i olika teman med underkategorier, detta tillät undersökningen att jämföra resultatet från intervjuerna med aktuell forskning. Utifrån slutsatsen har studien tagit fram ett förslag på en konceptuell modell för hur acceptans av digitala verktyg skulle kunna se ut. / Today, more and more people come into contact with new digital technologies both in their profession but also privately. It is therefore more important than ever that digital tools meet the end-users’ expectations and requirements. The purpose of this research was to explore the phenomenon of digital acceptance. Therefore, models and theories for evaluation were selected to be compared against the individual's experience and acceptance of digital tools. A theoretical foundation was created by collecting and analyzing nine models for evaluation of systems and user acceptance, where three were selected. The research was conducted with the help of interviews where participants from different professional backgrounds were given the opportunity to talk about their experiences with digitalization. The material from these interviews was then analyzed and categorized into different themes with subcategories, this allowed the research to compare the results from the interviews with current research. Based on the conclusion, the research has produced a proposal with a conceptual model for what acceptance of digital tools could look like.

Personliga data samlas in när vi besöker internetsidor och tillgång till personliga data har snabbt fåttavgörande betydelse för alltfler företags värdeskapande. Därför har metodutveckling för tillgång tillpersonliga data blivit en central del i företags konkurrenskraft. Det medför emellertid stora och riskerför individers personliga integritet. För att motverka sådana risker infördes 2018 den europeiskadataskyddsförordningen (GDPR). Vår analys visar att GDPR ger ett stort tolkningsutrymme för hurföretag informerar om datainsamling via cookie-notifikationer. Utformningen varierar därför kraftigtoch designas ofta för att styra användare mot att acceptera datainsamling. Vår analys visar att eneffekt av GDPR är att antalet cookie-notifikationer ökat avsevärt och att individers medvetenhet omoch oro inför hur personliga data samlas in och används har ökat efter GDPR:s införande. Däremotpekar våra resultat på att GDPR inte haft några betydande effekter på användares beteende när detgäller att aktivt skydda sina personliga data. De viktigaste skälen till att GDPR inte haft några effekterpå användarnas beteende för att skydda sina personliga data är att det är alltför tidskrävande och svårt.Vår analys visar därför att det så kallade “informerade samtycket” till insamling av personliga datainte effektivt uppnås trots GDPR:s införande. Vår slutsats för fortsatt forskning är att det är angelägetmed fördjupad forskning kring obalanser mellan individer, företag och reglerande myndigheterkopplat till hur personliga data samlas in, sammanställs och används. / The collection of personal data has become a crucial part of companies value creation. Because ofthat, the development of methods to get access to power over the personal data has become a centralpart in the competitiveness between companies. This has resulted in risks and concerns concerningindividual privacy. To counteract these risks, the European Union introduced the General dataProtection Regulation (GDPR). Our analysis shows that one effect of the GDPR is an increased usageof cookie-notifications when informing users of data collection. Our analysis also shows that theregulation has room for interpretation for how the companies inform the user about data collectionpractices. That has resulted in varied design methods in cookie-notifications that often steer userstowards an acceptance of collection of personal data. Because of the increased usage of cookienotificationsusers awareness and privacy concerns has drastically increased. However, our findingsshow that the regulation hasn’t had an effect on user behavior, specifically connected to protectingtheir personal data online. The main reasons for this are that it takes a lot of effort and time tocomprehend how that is done practically. Therefore, our analysis shows that “informed consent” isnot effectively achieved in the current methods, despite it being required in the regulation. Ourconclusion is therefore that future research should focus on the imbalance between individuals,companies and regulatory instances when addressing the problems with collection and usage of personal data.

Idag kommer fler och fler i kontakt med nya digitala tekniker både inom yrket men även privat. Det är därför viktigare än någonsin att de digitala verktygen når upp till slutanvändares förväntningar såväl som krav. Syftet med denna studien var att undersöka fenomenet digital acceptans. Därför valdes modeller och teorier för utvärdering ut för att jämföras mot individens upplevelser och acceptans av digitala verktyg. En teoretisk grund har lagts genom att samla in och analysera nio modeller för utvärdering av system och användaracceptans, där tre modeller valdes ut. Studien har genomförts med hjälp av intervjuer där respondenter från olika yrkesbakgrunder har fått möjligheten att berätta om sina upplevelser kring digitaliseringen. Materialet från dessa intervjuer har därefter analyserats för att kategoriseras i olika teman med underkategorier, detta tillät undersökningen att jämföra resultatet från intervjuerna med aktuell forskning. Utifrån slutsatsen har studien tagit fram ett förslag på en konceptuell modell för hur acceptans av digitala verktyg skulle kunna se ut. / Today, more and more people come into contact with new digital technologies both in their profession but also privately. It is therefore more important than ever that digital tools meet the end-users’ expectations and requirements. The purpose of this research was to explore the phenomenon of digital acceptance. Therefore, models and theories for evaluation were selected to be compared against the individual's experience and acceptance of digital tools. A theoretical foundation was created by collecting and analyzing nine models for evaluation of systems and user acceptance, where three were selected. The research was conducted with the help of interviews where participants from different professional backgrounds were given the opportunity to talk about their experiences with digitalization. The material from these interviews was then analyzed and categorized into different themes with subcategories, this allowed the research to compare the results from the interviews with current research. Based on the conclusion, the research has produced a proposal with a conceptual model for what acceptance of digital tools could look like.

Les services Internet populaires modèlent et remodèlent fondamentalement les moyens traditionnels de communication des personnes, ayant ainsi un impact majeur sur leur vie sociale. Deux des services Internet très populaires avec cette caractéristique sont les Réseaux sociaux en ligne (OSN) et les systèmes Peer-to-Peer (P2P). Les ONS fournissent un environnement virtuel où les gens peuvent partager leurs informations et leurs intérêts tout en étant en contact avec d'autres personnes. D'autre part, les systèmes P2P, qui sont toujours l'un des services populaires avec une grande proportion de l'ensemble du trafic Internet, offrent une occasion en or pour leurs clients de partager un type de contenu différent, y compris le contenu protégé. En dehors de l'énorme popularité des ONS et des systèmes de P2P parmi les utilisateurs réguliers, ils sont intensivement utilisés par les professionnels (grandes entreprises, politiciens, athlètes, célébrités en cas d'ONS et éditeurs de contenu professionnels en cas de P2P) afin d'interagir avec les gens à des fins différentes (campagnes marketing, les commentaires des clients, amélioration de la réputation publique, etc.) Dans cette thèse, nous caractérisons le comportement des utilisateurs réguliers et professionnels dans les deux services mentionnés populaires (ONS et P2P) en termes de stratégies de publication, de consommation de contenu et d'analyse comportementale. À cette fin, cinq de nos études menées sont présentées dans ce manuscrit comme suit: - "L'évolution des contenus multimédias", qui présente une analyse approfondie sur l'évolution du contenu multimédia disponible en BitTorrent en se concentrant sur quatre mesures pertinentes à travers différentes catégories de contenu : la disponibilité du contenu, la popularité du contenu, la taille de contenu et les commentaires de l'utilisateur - "La réaction des utilisateurs professionnels face aux actions de lutte contre le piratage", en examinant l'impact de deux grandes actions de lutte contre le piratage - la fermeture de Megaupload et la mise en œuvre de la loi anti-piratage française (HADOPI) - sur le comportement des publicateurs professionnels dans le plus grand portail de BitTorrent qui sont les principaux fournisseurs de contenu en ligne protégé. - "La quantité d'informations divulguées sur Facebook", en enquêtant sur l'exposition publique des profils utilisateurs, une grande base de données comprenant un demi-million d'utilisateurs réguliers. - "Les utilisateurs professionnels Cross Posting Activity», en analysant le modèle de publication des utilisateurs professionnels de mêmes informations sur trois grands ONS à savoir Facebook, Google+ et Twitter. - "Les stratégies des utilisateurs professionnels dans les ONS", où nous étudions la stratégie globale d'utilisateurs professionnels par secteur (par exemple, les entreprises de voitures, l'habillement, politiques, etc.) sur Facebook, Google+ et Twitter. Les résultats de cette thèse fournissent une vision d'ensemble pour comprendre certains aspects comportementaux importants de différents types d'utilisateurs des services Internet populaires et ces contributions peuvent être utilisées dans divers domaines (par exemple analyse de campagne marketing et publicité, etc.) et les différentes parties peuvent bénéficier des résultats et des méthodologies mises en œuvre telles que les FAI et les propriétaires des services pour leur planification ou l'expansion des services actuels à venir, ainsi que les professionnels pour accroître leur succès sur les médias sociaux / Popular Internet services are fundamentally shaping and reshaping traditional ways of people communication, thus having a major impact on their social life. Two of the very popular Internet services with this characteristic are Online Social Networks (OSNs) and Peer-to-Peer (P2P) systems. OSNs provide a virtual environment where people can share their information and interests as well as being in contact with other people. On the other hand, P2P systems, which are still one of the popular services with a large proportion of the whole Internet traffic, provide a golden opportunity for their customers to share different type of content including copyrighted content. Apart from the huge popularity of OSNs and P2P systems among regular users, they are being intensively used by professional players (big companies, politician, athletes, celebrities in case of OSNs and professional content publishers in case of P2P) in order to interact with people for different purposes (marketing campaigns, customer feedback, public reputation improvement, etc.). In this thesis, we characterize the behavior of regular and professional users in the two mentioned popular services (OSNs and P2P systems) in terms of publishing strategies, content consumption and behavioral analysis. To this end, five of our conducted studies are presented in this manuscript as follows: - “The evolution of multimedia contents", which presents a thorough analysis on the evolution of multimedia content available in BitTorrent by focusing on four relevant metrics across different content categories: content availability, content popularity, content size and user's feedback. - “The reaction of professional users to antipiracy actions", by examining the impact of two major antipiracy actions, the closure of Megaupload and the implementation of the French antipiracy law (HADOPI), on professional publishers behavior in the largest BitTorrent portal who are major providers of online copyrighted content. - “The amount of disclosed information on Facebook", by investigating the public exposure of Facebook users' profile attributes in a large dataset including half million regular users. - “Professional users Cross Posting Activity", by analyzing the publishing pattern of professional users which includes same information over three major OSNs namely Facebook, Google+ and Twitter. - “Professional Users' Strategies in OSNs", where we investigate the global strategy of professional users by sector (e.g., Cars companies, Clothing companies, Politician, etc.) over Facebook, Google+ and Twitter. The outcomes of this thesis provide an overall vision to understand some important behavioral aspects of different types of users on popular Internet services and these contributions can be used in various domains (e.g. marketing analysis and advertising campaign, etc.) and different parties can benefit from the results and the implemented methodologies such as ISPs and owners of the Services for their future planning or expansion of the current services as well as professional players to increase their success on social media