Understanding the dynamics of social interactions is crucial to comprehend human behavior. The emergence of online social media has enabled access to data regarding people relationships at a large scale. Twitter, specifically, is an information oriented network, with users sharing and consuming information. In this work, we study whether users tend to be in contact with people interested in similar topics, i.e., if they are topically aligned. To do so, we propose an approach based on the use of hashtags to extract information topics from Twitter messages and model users'interests. Our results show that, on average, users are connected with other users similar to them. Furthermore, we show that topical alignment provides interesting information that can eventually allow inferring users' connectivity. Our work, besides providing a way to assess the topical similarity of users, quantifies topical alignment among individuals, contributing to a better understanding of how complex social systems are structured.
The advances of multimedia models and tools popularized the access and production of multimedia contents: in this new scenario, there is no longer a clear distinction between authors and end-users of a production. These user-authors often work in a collaborative way. As end-users, they collectively participate in interactive environments, consuming multimedia arti-
The Web is evolving from a space for publication/consumption of documents to an environment for collaborative work, where digital content can travel and be replicated, adapted, decomposed, fusioned, and transformed. We call this the Fluid Web perspective. This view requires a thorough revision of the typical document-oriented approach that permeates content management on the Web. This paper presents our solution for the Fluid Web, which allows moving from the document-oriented to a content-oriented perspective, where "content" can be any digital object. The solution is based on two axes: a self-descriptive unit to encapsulate any kind of content artifact-the Digital Content Component (DCC) and a Fluid Web infrastructure that provides management and deployment of DCCs through the Web, and whose goal is to support collaboration on the Web. Designed to be reused and adapted, DCCs encapsulate data and software using a single structure, thus allowing homogeneous composition and processing of any digital content, executable or not. These properties are exploited by our Fluid Web infrastructure, which supports DCC multilevel annotation and discovery mechanisms, configuration management, and version control. Our work extensively explores taxonomic ontologies and Semantic Web standards, which serve as a semantic bridge, unifying DCC management vocabularies, and improving DCC description/indexing/discovery. DCCs and infrastructure have been implemented and are illustrated by means of a running example, for a scientific application.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.