Data-Driven Text Generation using Neural Networks & Provenance is Complicated and Boring — Is there a solution?

Title: Data-Driven Text Generation using Neural Networks Speaker: Pavlos Vougiouklis, University of Southampton Abstract: Recent work on neural networks shows their great potential at tackling a wide variety of Natural Language Processing (NLP) tasks. This talk will focus on the Natural Language Generation (NLG) problem and, more specifically, on the extend to which neural network language models could be employed for context-sensitive and data-driven text generation. In addition, a neural network architecture for response generation in social media along with the training methods that enable it to capture contextual information and effectively participate in public conversations will be discussed. Speaker Bio: Pavlos Vougiouklis obtained his 5-year Diploma in Electrical and Computer Engineering from the Aristotle University of Thessaloniki in 2013. He was awarded an MSc degree in Software Engineering from the University of Southampton in 2014. In 2015, he joined the Web and Internet Science (WAIS) research group of the University of Southampton and he is currently working towards the acquisition of his PhD degree in the field of Neural Network Approaches for Natural Language Processing. Title: Provenance is Complicated and Boring — Is there a solution? Speaker: Darren Richardson, University of Southampton Abstract: Paper trails, auditing, and accountability — arguably not the sexiest terms in computer science. But then you discover that you've possibly been eating horse-meat, and the importance of provenance becomes almost palpable. Having accepted that we should be creating provenance-enabled systems, the challenge of then communicating that provenance to casual users is not trivial: users should not have to have a detailed working knowledge of your system, and they certainly shouldn't be expected to understand the data model. So how, then, do you give users an insight into the provenance, without having to build a bespoke system for each and every different provenance installation? Speaker Bio: Darren is a final year Computer Science PhD student. He completed his undergraduate degree in Electronic Engineering at Southampton in 2012.

Understanding social media in everyday life: Ethnomethodological and conversation analytic perspectives

Over the last decade, social media has become a hot topic for researchers of collaborative technologies (e.g., CSCW). The pervasive use of social media in our everyday lives provides a ready source of naturalistic data for researchers to empirically examine the complexities of the social world. In this talk I outline a different perspective informed by ethnomethodology and conversation analysis (EMCA) - an orientation that has been influential within CSCW, yet has only rarely been applied to social media use. EMCA approaches can complement existing perspectives through articulating how social media is embedded in everyday life, and how its social organisation is achieved by users of social media. Outlining a possible programme of research, I draw on a corpus of screen and ambient audio recordings of mobile device use to show how EMCA research can be generative for understanding social media through concepts such as adjacency pairs, sequential context, turn allocation / speaker selection, and repair. In doing so, I also raise questions about existing studies of social media use and the way they characterise interactional phenomena.