The proliferation of social media, such as blogs, micro-blogs and social networks, has led to a plethora of readily available user-generated content. The latter offers a unique, uncensored window into emerging stories and events, ranging from politics and revolutions to product perception and the zeitgeist. Importantly, structured information is available for user-generated content, by dint of its metadata, or can be surfaced via recently commoditized information extraction tools. This wealth of information, in the form of real-world entities and facts mentioned in a document, author demographics, and so on, provides exciting opportunities for mining insights from this content. Capitalizing upon these, we develop Grapevine, an online system that distills information from the social media collective on a daily basis, and facilitates its interactive exploration. To further this goal, we address important research problems, which are also of independent interest. The sheer scale of the data being processed, necessitates that our solutions be highly efficient. We propose efficient techniques for mining important stories, on a per-user-demographic basis, based on named entity co-occurrences in user-generated content. Building upon these, we propose efficient techniques for identifying emerging stories as-they-happen, by identifying dense structures in an evolving entity graph. To facilitate the exploration of these stories, we propose efficient techniques for filtering them, based on users’ textual descriptions of the entities involved. These gathered insights need to be presented to users in a useful manner, via a diverse set of representative documents; we thus propose efficient techniques for addressing this problem. Recommending related stories to users is important for navigation purposes. As the way in which these are related to the story being explored is not always clear, we propose efficient techniques for generating recommendation explanations via entity relatedness queries.

Consumer-generated reviews play an important role in online purchase decisions for many consumers. However, the quality and helpfulness of online reviews varies significantly. In addition, the helpfulness of different consumer-generated reviews is not disclosed to consumers unless they carefully analyze the overwhelming number of available contents. Therefore, it is of vital importance to develop predictive models that can evaluate online product reviews efficiently and then display the most useful reviews to consumers, in order to assist them in making purchase decisions. This thesis examines the problem of building computational models for predicting whether a consumer-generated review is helpful based on consumers' online votes on other reviews (where a consumer's vote on a review is either HELPFUL or UNHELPFUL), with the aim of suggesting the most suitable products and vendors to consumers.In particular, we propose in this thesis three different helpfulness prediction approaches for consumer-generated reviews. Our entropy-based approach is relatively simple and suitable for applications requiring simple recommendation engine with fully-voted reviews. However, our entropy-based approach, as well as the existing approaches, lack a general framework and are all limited to utilizing fully-voted reviews. We therefore present a probabilistic helpfulness prediction framework to overcome these limitations. To demonstrate the versatility and flexibility of this framework, we propose an EM-based model and a logistic regression-based model. We show that the EM-based model can utilize reviews voted by a very small number of voters as the training set, and the logistic regression-based model is suitable for real-time helpfulness predicting of consumer-generated reviews. To our best knowledge, this is the first framework for modeling review helpfulness and measuring the goodness of models. Although this thesis primarily considers the problem of review helpfulness prediction, the presented probabilistic methodologies are, in general, applicable for developing recommender systems that make recommendation based on other forms of user-generated contents.

Uppkomsten av dagens Web 2.0 har skapat möjligheter till större interaktivitet hos användarna. Denna utveckling har även följts av en möjlighet att skapa användargenererat innehåll, ett fenomen som benämns User Generated Content (UGC). En av de viktigaste aspekterna inom UGC är att det måste uppnå en god användbarhet, men likväl måste tjänsterna också erbjuda en rik subjektiv upplevelse. Denna subjektiva upplevelse benämns som User Experience och är ett uttryck för den upplevelse och tillfredställelse en användare känner då den ställs inför ett interaktivt gränssnitt. Syftet med uppsatsen var att identifiera User Experience av UGC-tjänster. Uppsatsen karaktäriseras av en kvalitativ ansats och grundar sig i en explorativ undersökning med loggböcker och intervjuer, där nio respondenters upplevelser ligger till grund för uppsatsens resultat. Uppsatsen bidrar med en modell över User Experience mål för UGC-tjänster. Modellen bidrar till en ökad förståelse för vad som utgör en god User Experience av en UGC-tjänst och kan på så vis vara vägledande för de som designar dessa typer av tjänster.

Large-scale socially-generated metadata is one of the key features driving the growth and success of the emerging Social Web. Recently there have been many research efforts to study the quality of this metadata - like user-contributed tags, comments, and ratings - and its potential impact on new opportunities for intelligent information access. However, much existing research relies on quality assessments made by human experts external to a Social Web community. In the present study, we are interested in understanding how an online community itself perceives the relative quality of its own user-contributed content, which has important implications for the successful selfregulation and growth of the Social Web in the presence of increasing spam and a flood of Social Web metadata. We propose and evaluate a machine learning-based approach for ranking comments on the Social Web based on the community's expressed preferences, which can be used to promote high-quality comments and filter out low-quality comments. We study several factors impacting community preference, including the contributor's reputation and community activity level, as well as the complexity and richness of the comment. Through experiments, we find that the proposed approach results in significant improvement in ranking quality versus alternative approaches.

Earthquake and submarine mass failure are the most frequent causes of tsunami waves. While the process of the tsunami generation by earthquakes is reasonably well understood, the generation of tsunami waves during submarine mass failure is not. Estimates of the energy released during a tsunamigenic earthquake and respective tsunami wave draw a clear picture of the efficiency of the tsunami-generating process. However for submarine landslides, this is not as straightforward because the generation process has never been recorded in nature making energy inferences very difficult. Hence the efficiency of submarine landslide as tsunami generators is yet to be conclusively determined. As the result of this uncertainty, different equations, derived from experimental data or theory, result in leading-wave amplitude that vary over 6 orders of magnitude for the same initial slide conditions. To arrive at more robust estimates of the leading-wave characteristics and associated runup, the spatiotemporal dynamics of the coupling between the slide body and water column needs to be investigated. The duration the water surface deformation is coupled with the slide motion is an essential question to shed light on the energy transfer. A parametric study is conducted with the state of-the-art hydrocode iSALE in order to shed light on this complex geophysical event. The mass, viscosity, and depth of submergence are the particular slide parameters varied and their relationship to runup and decoupling time is analyzed.

The objective of this study is to apply Computer-generated imagery for knowledge and skills in daily life. There are some Computer-generated imagery study on traditional education training; however, fewer professional image processing courses of Synchronous Learning Networking are carried out in practice. The feasibility of using lecture video or practice on line in teaching Computer-generated imagery concepts is important. How do teachers examine students¡¦ performance and make good use of Synchronous Learning Networking? In this study, we will propose the following dimensions to discuss: (1) the difference on Computer-generated imagery between Synchronous Learning Networking and traditional teaching (2) the difficulty on Computer-generated imagery when teaching and learning (3) how to make better performance on Computer-generated imagery under Synchronous Learning Networking. Comparative Case Study is conducted at Tainan Training Center and LMS (Learning Management System) of K12 digital school for the adults who actively study Computer-generated imagery by the means of traditional learning and E-learning. We put Computer-generated imagery under traditional teaching and Synchronous Learning Networking, and we make questionnaires for examining the detailed factors regarding to the performance of Computer-generated imagery.The results indicates that lecture on Synchronous Learning Networking is something about practice on line, whiteboard, slides show, top desk share and homepage browse with office hours and paper work in replace of real discussion. Sometimes teachers and students are meeting the information and interaction delay under Synchronous Learning Networking. Therefore, we are offering seven suggestions to get Computer-generated imagery under Synchronous Learning Networking improved: (1) Teachers suggest that the standard of hardware and Net environment is required. (2) Students should develop active attitude for learning under Synchronous Learning Networking. (3) Teachers should perform on line teaching and stream video is auxiliary. (4) Multiple material for the topic is available for students to choose and adjust their learning model. (5) Dividing into groups is not good for teaching and office hour or guest board is much better for discussion and interaction. (6) Teachers should create new Computer-generated imagery courses to inspire students¡¦ motivation. (7) Continued materials and platform for students to review and interact are required.

In this thesis we will discuss the subject of user participation in the development process of products, specifically video games, through a concept called User-generated content. Product development demands speed and flexibility in the development process and it has been suggested that managers should revise the process of product development to become more flexible and integrate the consumer in increasingly more steps of the process. Video games will often be modified after its release. In fact, it has been estimated that between 95% and 100% of the files in most software will be modified after its initial release. User participation, referring to behaviors and activities performed in a system development process, is a definite feature for websites that consider their content user-generated. Customers who participate in online video game UGC are actively changing games, modifying existing content and creating new content related to all aspects of the game bit by bit, while also contributing this content to others, usually over the internet through some sort of video game content sharing site.User participation is determined by a user’s ability to participate and his motivation to do so, the latter of which is the focus of this thesis. Two major branches of study can be distinguished from motivational theory; intrinsic motivation and extrinsic motivation. The main purpose of this thesis is to examine the effects of motivational factors of intrinsic motivation, extrinsic motivation and toolkits that motivate customers to participate in UGC for video games. We examine what effects intrinsic motivational factors enjoyment, altruism and continuance commitment, as well as extrinsic motivational factors rewards, future rewards, personal need and reputation have on user participation. The toolkits approach to product development is a common user-oriented product development methods in the video game industry, which allows users to modify and create content for games. We will also study what effects the usefulness and ease of use of these toolkits have on user participation. Conducting a quantitative study, we presented a questionnaire to members of four online video game UGC communities; Steam Workshop, GameBanana, ModDB and MODSonline, in order to assess users’ attitudes of aforementioned concepts in relation to their user participation.We have not found any relevant research that examines both motivational factors’ and toolkits’ effects on user participation in video game UGC. With recent turbulent developments in the video game industry regarding monetary compensation for UGC, we decided to put great weight on this area in this thesis, both through our review of previous literature and regarding the results of our study.Our multiple regression analysis showed that toolkit ease of use, intrinsic motivational factors enjoyment and altruism, as well as extrinsic motivational factor reputation have significant positive effects on user participation, while toolkit usefulness showed a significant negative effect on user participation. We also find trends suggesting the positive effect of continuance commitment on user participation, and, finally, a trend suggesting the negative effect of rewards on user participation.

Over the past decade, the networked information environment has increased consumers’ autonomy and brought radical change to the advertising industry. Now individual consumers can reach millions of others around the world and advise them on well-known brands through home-produced video-ads, which was not as accessible in a previous era dominated by one-way marketing. The overall objective of this thesis was to examine the attitudinal, behavioural and recall effects of consumer-generated advertising (CGA) on viewing audiences. This was achieved by implementing an exploratory sequential mixed method design. During an initial qualitative phase with focus groups, seven determinants of CGA effectiveness were identified: recognition of consumer-generated advertising; advertising quality; product involvement; perceived expertise of ad creators; motivations of ad creators; scepticism towards CGA; and consumer’s creativity. The Salience-Involvement model of CGA effects was then developed and tested in two subsequent empirical studies. Study One used a 2 x 2, between-subjects experimental design in which levels of advertising Source Salience (consumer-generated vs. company-generated) and Product Involvement (low vs. high involvement) were manipulated. Results reveal a largely negative impact of salient CGA when the consumer source was not disclosed. However, under high involvement conditions, amateur CGA was more entertaining and more likely to be electronically shared with others. Meanwhile, under low involvement, brands from consumer-generated ads showed higher levels of recall. Study Two investigated how the outcomes of professional and amateur CGA change after source disclosure using a 3 x 2 x 2, between-subjects design. In this experiment, levels of Source Awareness (consumer-generated ads vs. company ads vs. no source indicated) were manipulated in addition to Source Salience and Product Involvement. Findings show that Source Awareness produces an interactive effect with Source Salience and Product Involvement, which is significant only on the Cognitive component of Attitude towards the ad and the Attractiveness component of Credibility. Thus, disclosure of consumer source is likely to enhance ad evaluations when the CGA is professionally produced and involvement is low. Meanwhile, attribution of amateur CGA to consumer source is likely to have a negative impact. Conversely, attribution of an amateur ad to company source has a favourable attitudinal effect under high involvement. In summary, this research demonstrates that in the context of CGA, the communicator-receiver similarity does not necessarily guarantee a positive response. Most importantly, the CGA’s outcome is moderated by Source Salience. Since Source Salience specifically characterises the consumer source in this context, it could potentially add another dimension to the traditional conceptualisation of the information source.

Certifiers have a crucial role in facilitating effective communication in the online and the traditional world. As a way of generating statistically meaningful information, certification has been adopted in financial statements evaluation and more recently in various online communities as well. This dissertation examines three related issues along this common theme: online reputation market, moderation in user-generated content, and strategic communications in the market for certifications, and consists of three essays. The first essay analyzes the impact of various dispute mechanisms on online identity trading. Online identities with a good reputation profile is a valuable and tradable asset. However, with free identity creation, there is room for low quality sellers to free-ride high quality sellers. When there is a lack of incentive for sellers to maintain a good reputation, identity trading becomes ineffective. This essay focuses on the role of an auditing system, such as eBay dispute center, and shows that even a small amount of objective information from the auditors can reverse the negative result and sustain reliable reputation and identity trading. The second essay investigates the impact of moderation on the quality of information in an user-generated content (UGC) environment. In most UGC communities, content contributors have incentive to publish biased or false information. For example, companies hire people to write positive reviews about themselves. This essay establishes a framework for the mechanism design of moderation, and provides insight on how to optimally allocate moderation resource. The third essay examines a market for certification and certifiers' strategic reporting behaviors. The central question is how to induce certifiers to provide statistically meaningful information to investors when they are paid by their client firms. We provide insights on how certifier competition plays an role in firms' certifier choice, how certifiers degrade their accuracies to achieve maximum profit, and how the legal environment impacts the information quality. / text

The following report defines the concept of conspicuous participation and it demonstrates how it impacts nonprofit marketing efforts through social media. This is accomplished through providing an in-depth theoretical background, a detailed typography describing how conspicuous participation is currently being used to promote interactions with nonprofit organizations, and through two case studies, which offer real-world examples of how nonprofit organizations are utilizing this concept. Conspicuous participation can be defined as The act of publishing original or existing content in an online space that is visible to others, either all members of the general public or members of a private social network, in order to interact with and/or show support for a defined community or organization. / text