Content quality assessment related frameworks for social media

The assessment of content quality (CQ) in social media adds a layer of complexity over traditional information quality assessment frameworks. Challenges arise in accurately evaluating the quality of content that has been created by users from different backgrounds, for different domains and consumed by users with different requirements. This paper presents a comprehensive review of 19 existing CQ assessment related frameworks for social media in addition to proposing directions for framework improvements

Method for analyzing web space data

A method for analyzing data from the web that determine the importance that a chosen subject has in society, e.g., subject matter relating a concert, a scientific discovery, a football match, a person, a corporation, a brand, or a car, and analyze such data that can represent the entire society better than the known techniques. The method according to the invention can avoid malicious alterations and is able to measure and detect the temporal relations among all the web resources that talk about a particular topic or subject matter

Blog Style Classification: Refining Affective Blogs

In the constantly growing blogosphere with no restrictions on form or topic, a number of writing styles and genres have emerged. Recognition and classification of these styles has become significant for information processing with an aim to improve blog search or sentiment mining. One of the main issues in this field is detection of informative and affective articles. However, such differentiation does not suffice today. In this paper we extend the differentiation and suggest a fine-grained set of subcategories for affective articles. We propose and evaluate a classification method employing novel lexical, morphological, lightweight syntactic and structural features of written text. The results show that our method outperforms the existing approaches

Large-scale document labeling using supervised sequence embedding

A critical component in computational treatment of an automated document labeling is the choice of an appropriate representation. Proper representation captures specific phenomena of interest in data while transforming it to a format appropriate for a classifier. For a text document, a popular choice is the bag-of-words (BoW) representation that encodes presence of unique words with non-zero weights such as TF-IDF. Extending this model to long, overlapping phrases (n-grams) results in exponential explosion in the dimensionality of the representation. In this work, we develop a model that encodes long phrases in a low-dimensional latent space with a cumulative function of individual words in each phrase. In contrast to BoW, the parameter space of the proposed model grows linearly with the length of the phrase. The proposed model requires only vector additions and multiplications with scalars to compute the latent representation of phrases, which makes it applicable to large-scale text labeling problems. Several sentiment classification and binary topic categorization problems will be used to empirically evaluate the proposed representation. The same model can also encode relative spatial distribution of elements in higher-dimensional sequences. In order to verify this claim, the proposed model will be evaluated on a large-scale image classification dataset, where images are transformed into two-dimensional sequences of quantized image descriptors.Ph.D., Computer Science -- Drexel University, 201

Aspects of the self: an analysis of self reflection, self presentation and the experiential self within selected Buddhist blogs

At the heart of this dissertation is an examination of self reflection, self presentation and the experiential self within three Buddhist blogs: The Buddhist Blog, The American Buddhist and ThinkBuddha.org. Based upon this original research, my thesis contributes to ongoing discussions relating to the self online and to the emerging field of media, religion and culture. A number of other scholars have already investigated how the internet has provided a new platform in which to engage with online religious communities, participate in rituals and develop religious identity. Up to this point, however, the place of Buddhism online has been largely overlooked or limited to purely descriptive analysis. As I argue in chapter one, this thesis provides a more developed examination of Buddhism on the internet. In chapters two and three, I demonstrate how my analysis and definition of three aspects of the self, namely self reflection, self presentation and the experiential self, within selected Buddhist blogs (online diaries) provides an innovative contribution to the developing area of study related to new media and religion. In chapter four, I consider my four central research questions and the interdisciplinary approach used which draws from the fields of anthropology, visual cultural studies, media studies, as well as Buddhist studies. In chapter five I present the Buddhist interpretative framework used for the analysis of the experiential self. This focuses on the conceptual issues of the self in early Buddhism as well as the Buddhist Theravada Abhidhamma framework for the analysis of the self (anatta), the components of the self (khandhas) and the senses and sense spheres (ayatanas and dhatus). Through the three ethnographic case studies (chapters six, seven and eight) I demonstrate how the genre of life writing (blogs) is used as a medium for self reflection, self presentation and the experiential self, thus emphasising the experiential aspect of human existence online. In the conclusion (chapter nine), I consider the continuities and discontinuities between the three blogs, and in doing so I illustrate how the detailed examination of Buddhist blogs provides an insight into different aspects of popular culture, of Buddhism on the internet and how new media is being used in the twenty first century