This book is the first to present a comprehensive theory of non-canonical questions, those question types that do not (only) request information from the addressee, but rather (additionally) tell us something about the speaker's epistemic and/or emotional state, such as can't-find-the-value questions, echo questions, rhetorical questions, and surprise questions. While much recent research has explored the formal semantics and the phonetics and phonology of both canonical and non-canonical questions, the literature is still lacking a comprehensive account from a syntax-pragmatics perspective that brings together the multiple findings and strands of research from the last twenty years. The standard view in the syntax-pragmatics literature is that most special interpretations of non-canonical questions involve syntactic projections at or even above the level of illocutionary force. In this work, Andreas Trotzke argues that this approach is a mistake, and proposes a new alternative theory of non-canonical questions in which both their special pragmatics and their syntax, as well as in many cases their emotive component, can be derived solely from propositional-level operators that do not affect the illocutionary level of utterances and can be found across illocutionary forces. This account dramatically simplifies the syntactic analysis of non-canonical questions and is also able to capture some previously unobserved data in the discourse behavior of those question types.

Social media sites are one of the most popular destinations in today's online world. With millions of users visiting social networking sites like Facebook, YouTube, Twitter etc. every day to share social content at their disposal; from simple textual information about what they are doing at any moment of time, to opinions regarding products, people, events, movies to videos and music, these sites have become massive sources of user generated content. In this work we focus on one such social networking site - Twitter, for the task of information extraction and sentiment analysis. This work presents a linguistic framework that first performs syntactic normalization of tweets on top of traditional data cleaning, extracts assertions from each tweet in the form of binary relations, and creates a contextualized knowledge base (KB). We then present a Language Model (LM) based classifier trained on a small set of manually tagged corpus, to perform sentence level sentiment analysis on the collected assertions to eventually create a KB that is backed by sentiment values. We use this approach to implement a contextualized sentiment based yes/no question answering system.

As phraseology moves ever more into the mainstream of corpus linguistics research, it is no longer acceptable to limit the language studied to canonical, dictionary citation forms. But how can others be retrieved, when precise forms they take are not known? This paper sets out some general principles for retrieving non-canonical examples, using collocational frameworks, and expands upon the utility of analysing the innovative alongside the ordinary.

This book provides latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to intelligent social networks and collaborative systems, intelligent networking systems, mobile collaborative systems, secure intelligent cloud systems, etc., as well as to reveal synergies among various paradigms in such a multi-disciplinary field intelligent collaborative systems. With the fast development of the Internet, we are experiencing a shift from the traditional sharing of information and applications as the main purpose of the Web to an emergent paradigm, which locates people at the very centre of networks and exploits the value of people's connections, relations and collaboration. Social networks are also playing a major role in the dynamics and structure of intelligent Web-based networking and collaborative systems. Virtual campuses, virtual communities and organizations strongly leverage intelligent networking and collaborative systems by a great variety of formal and informal electronic relations, such as business-to-business, peer-to-peer and many types of online collaborative learning interactions, including the emerging e-learning systems. This has resulted in entangled systems that need to be managed efficiently and in an autonomous way. In addition, latest and powerful technologies based on grid and wireless infrastructure as well as cloud computing are currently enhancing collaborative and networking applications a great deal but also facing new issues and challenges. The principal purpose of the research and development community is to stimulate research that will lead to the creation of responsive environments for networking and, at longer-term, the development of adaptive, secure, mobile and intuitive intelligent systems for collaborative work and learning.