Social Computing Data Repository

Social Computing Data Repository hosts data from a collection of many different social media sites, most of which have blogging capacity. Some of the prominent social media sites included in this repository are BlogCatalog, Twitter, MyBlogLog, Digg, StumbleUpon, del.icio.us, MySpace, LiveJournal, The Unofficial Apple Weblog (TUAW), Reddit, etc. The repository contains various facets of blog data including blog site metadata like, user defined tags, predefined categories, blog site description; blog post level metadata like, user defined tags, date and time of posting; blog posts; blog post mood (which is defined as the blogger's emotions when (s)he wrote the blog post); blogger name; blog post comments; and blogger social network.

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.

Marketing Using Social Media - Tom Chapman - Headstream

This is a recording of a talk given on 12 March 2010 by Tom Chapman of Headstream, a marketing company who specialise in the use of digital social media to promote products and brands.

Review: Social Media and Abstract Nouns

The revision slides for our Social Media course, contains major lessons learned throughout the course, and an example exam question (on trust).

Social Media Analytics: Trust and Power

In this lecture for a second year interdisciplinary course (part of the curriculum innovation programme) We explore the scope of social media analytics and look at two aspects in depth: Analysing for influence (looking at factors such as network structure, propagation of content and interaction), and analysing for trust (looking at different methods including policy, provenance and reputation - both local and global). The lecture notes include a number of short videos, which cannot be included here for copy-write reasons.

Scalable real-time crisis mapping and analytics of social media streams for disaster management and breaking news

Real-time geoparsing of social media streams (e.g. Twitter, YouTube, Instagram, Flickr, FourSquare) is providing a new 'virtual sensor' capability to end users such as emergency response agencies (e.g. Tsunami early warning centres, Civil protection authorities) and news agencies (e.g. Deutsche Welle, BBC News). Challenges in this area include scaling up natural language processing (NLP) and information retrieval (IR) approaches to handle real-time traffic volumes, reducing false positives, creating real-time infographic displays useful for effective decision support and providing support for trust and credibility analysis using geosemantics. I will present in this seminar on-going work by the IT Innovation Centre over the last 4 years (TRIDEC and REVEAL FP7 projects) in building such systems, and highlights our research towards improving trustworthy and credible of crisis map displays and real-time analytics for trending topics and influential social networks during major news worthy events.

Bias in the Social Web

Abstract A frequent assumption in Social Media is that its open nature leads to a representative view of the world. In this talk we want to consider bias occurring in the Social Web. We will consider a case study of liquid feedback, a direct democracy platform of the German pirate party as well as models of (non-)discriminating systems. As a conclusion of this talk we stipulate the need of Social Media systems to bias their working according to social norms and to publish the bias they introduce. Speaker Biography: Prof Steffen Staab Steffen studied in Erlangen (Germany), Philadelphia (USA) and Freiburg (Germany) computer science and computational linguistics. Afterwards he worked as researcher at Uni. Stuttgart/Fraunhofer and Univ. Karlsruhe, before he became professor in Koblenz (Germany). Since March 2015 he also holds a chair for Web and Computer Science at Univ. of Southampton sharing his time between here and Koblenz. In his research career he has managed to avoid almost all good advice that he now gives to his team members. Such advise includes focusing on research (vs. company) or concentrating on only one or two research areas (vs. considering ontologies, semantic web, social web, data engineering, text mining, peer-to-peer, multimedia, HCI, services, software modelling and programming and some more). Though, actually, improving how we understand and use text and data is a good common denominator for a lot of Steffen's professional activities.

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.

Research on Social Network Sites

A bibliography of research on Social Network web sites. The research contained below is focused specifically on social network sites (or "social networking" sites). Some of this is connected to social media, social software, Web2.0, social bookmarking, educational technologies, communities research, etc. but this is not the organizing focus and not everything related to these other topics is included here. This list is not methodologically or disciplinarily organized. There is work here from communications, information science, anthropology, sociology, economics, political science, cultural studies, computer science, etc.

The Web 2.0 Development Survival Guide

Building software for Web 2.0 and the Social Media world is non-trivial. It requires understanding how to create infrastructure that will survive at Web scale, meaning that it may have to deal with tens of millions of individual items of data, and cope with hits from hundreds of thousands of users every minute. It also requires you to build tools that will be part of a much larger ecosystem of software and application families. In this lecture we will look at how traditional relational database systems have tried to cope with the scale of Web 2.0, and explore the NoSQL movement that seeks to simplify data-storage and create ultra-swift data systems at the expense of immediate consistency. We will also look at the range of APIs, libraries and interoperability standards that are trying to make sense of the Social Media world, and ask what trends we might be seeing emerge.

Mining Events from Multimedia streams, Jon Hare

peaker(s): Jon Hare Organiser: Time: 25/06/2014 11:00-11:50 Location: B32/3077 Abstract The aggregation of items from social media streams, such as Flickr photos and Twitter tweets, into meaningful groups can help users contextualise and effectively consume the torrents of information on the social web. This task is challenging due to the scale of the streams and the inherently multimodal nature of the information being contextualised. In this talk I'll describe some of our recent work on trend and event detection in multimedia data streams. We focus on scalable streaming algorithms that can be applied to multimedia data streams from the web and the social web. The talk will cover two particular aspects of our work: mining Twitter for trending images by detecting near duplicates; and detecting social events in multimedia data with streaming clustering algorithms. I'll will describe in detail our techniques, and explore open questions and areas of potential future work, in both these tasks.

What can Flickr photographs tell us about New York City?

In their second year, our undergraduate web scientists undertake a group project module (WEBS2002, led by Jonathon Hare & co-taught by Su White) in which they get to apply what they learnt in the first year to a practical web-science problem, and also learn about team-working. For the project this semester, the students were provided with a large dataset of geolocated images and associated metadata collected from the Flickr website. Using this data, they were tasked with exploring what this data could tell us about New York City. In this seminar the two groups will present the outcomes of their work. Team Alpha (Wil Muskett, Mark Cole & Jiwanjot Guron) will present their work on "An exploration of deprivation in NYC through Flickr". This work aims to explore whether social deprivation can be predicted geo-spatially through the analysis of social media by exploring correlations within the Flickr data against official statistics including poverty indices and crime rates. Team Bravo (Edward Baker, Callum Rooke & Rachel Whalley) will present their work on "Determining the Impact of the Flickr Relaunch on Usage and User Behaviour in New York City". This work explores the effect of the Flickr site relaunch in 2013 and looks at how user demographics and the types of content created by the users changed with the relaunch.