Suppor&ng a social media research environment by mining big textual data. Sophia Ananiadou Na-onal Centre for Text Mining

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1 Suppor&ng a social media research environment by mining big textual data Sophia Ananiadou Na-onal Centre for Text Mining

2 Mo-va-on Much social media data consists of unstructured, noisy natural language Analysis is challenging Simple tools only get you so far Complex RQs demand complex analysis ODen may not have a clear idea of what RQ is to start (e.g., public health issues) and need to explore, filter, link, transform, annotate, data Need to integrate with other types of data

3 NaCTeM Contribu-ons: tools, services, plakorms Ability to perform analy-cs at many levels (lexical, syntac-c, seman-c, pragma-c, ) Customisable tools Interoperable frameworks (U- Compare and Argo) to handle unstructured data Tools (including 3 rd party and Web Services) can be strung together easily (and results compared) Crowdsourcing, collabora-ve annota-on environment (Argo hqp://argo.nactem.ac.uk) Processing at large scale (EUPMC)

4 Contribu-ons: relevant experience Digging into Data Challenge (2011) - ISHER Search system End- users: social history researchers News reports on social unrest New York Times; 1.8 million ar-cles ( ) Includes deep analysis at level of event (e.g. conflict_event([par/cipants],/me,loca/on,casual /es) Extracts discourse informa.on for social history events

5 Discourse analy-cs An event may: represent a fact, a specific event, an opinion/analysis, a hypothe-cal situa-on, recommenda-on, etc. be presented as the author s own knowledge/point of view, or that of a third party be expressed together with a level of certainty (e.g., specula-on) Represent a situa-on in the past, an ongoing situa-on, or something that will happen in the future be negated, i.e., there is an indica-on that the event did not happen meta- knowledge

6 A past event A past event reported by a third party

7 A future event A planned event reported by a third party A negated, hypothe-cal event

8 A hypothe-cal event A future event with high, but not complete confidence

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14 NaCTeM Projects related with social sciences TwiQer analysis and poli-cal discourse analysis JISC funded Frame analysis (JISC) Opinion mining and sen-ment analysis projects (JISC) and OSSMETER (EU)

15 New projects ( ) Digging into Data AHRC, ESRC, JISC, NEH, Innova-on.Ca, Big Data Analy-cs Ins-tute and Social Media Laboratory Dalhousie Canada and BHL Mining the Biodiversity Heritage Library to create a Social Digital Library Leveraging social media sites, engaging a community of users to exploit the BHL as forum for exchange of ideas Integrated social media environment will support the forma-on and maintenance of new and online communi-es hqp://

16 New projects ( ) AHRC, Big Data Call Mining the History of Medicine Crea-ng resources, infrastructure and services for historians of medicine Using crowdsourcing for annota-on based on our plakorms Improving text mining tools across domains

17 New projects MRC with NICE ( ) Analysis of public health reviews- includes social aspects collabora-ve annota-on of evidence based reviews Social network of reviewers

18 Core techniques Terminology, event extrac-on, fact extrac-on, topic iden-fica-on Mul-- document summarisa-on Clustering (including assignment of meaningful cluster labels) Classifica-on (including against given scheme, e.g. Bri-sh Educa-on Thesaurus, HASSET)

19 Contribu-ons: beyond borders NaCTeM is the UK Hub for META- NET (Mul-lingual Europe Technology Alliance) SA execu-ve board of MetaNet Social media can be borderless Individuals can display mixed language behaviour

20 Contribu-ons: general Can also contribute in areas such as Resource building (seman-c resources, corpora) Trend detec-on Data linking via social network construc-on and analysis (DiD 2014) Detec-on of concept spreading Contextual interpreta-on Evalua-on and valida-on Detec-on of imposters/usurpers

21 Future vision Integra-ng social media content and providing tools and resources to foster a community of users exploi-ng a computa.onal social media research environment Providing mechanisms to share and cross- link digital objects between social media research sites Text mining using advanced seman-cs at the core of it Training for the next genera-on of computa-onal social science researchers

22 Related staff and projects People John McNaught Paul Thompson Yannis Korkontzelos Rafal Rak Riza Ba-sta- Navarro Jacob Carter Bill Black Makoto Miwa Related projects Digging into Data ISHER ISHER/ ASSERT ASSIST Digging into Data MIBIO/ Mining the History of Medicine EUPMC europepmc Meta- Net