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Worldwide impact on language learners and others has been generated by the development at Lancaster of a ground-breaking natural language processing tool (CLAWS4), and an associated unique collection of natural language data (the British National Corpus, or BNC). Some highlights selected from the primary impacts are as follows:
The pathways to impact have been primarily via consultancy and via licencing of software IP. The impact itself is largely on the language learners—i.e. users of products such as the above. There is a secondary economic impact on a UK SME which has licenced our software.
COnnecting REpositories (CORE) is a system for aggregating, harvesting and semantically enriching documents. As at July 2013, CORE contains 15m+ open access research papers from worldwide repositories and journals, on any topic and in more than 40 languages. In July 2013, CORE recorded 500k+ visits from 90k+ unique visitors. By processing both full-text and metadata, CORE serves four communities: researchers searching research materials; repository managers needing analytical information about their repositories; funders wanting to evaluate the impact of funded projects; and developers of new knowledge-mining technologies. The CORE semantic recommender has been integrated with digital libraries and repositories of cultural institutions, including the European Library and UNESCO. CORE has been selected to be the metadata aggregator of the UK's national open access services.
The Natural Language Toolkit (NLTK) is a widely-adopted Python library for natural language processing. NLTK is run as an open source project. Three project leaders, Steven Bird (Melbourne University), Edward Loper (BBN, Boston) and Ewan Klein (University of Edinburgh) provide the strategic direction of the NLTK project.
NLTK has been widely used in academia, commercial / non-profit organisations and public bodies, including Stanford University and the Educational Testing Service (ETS), which administers widely-recognised tests across more than 180 countries. NLTK has played an important role in making core natural language processing techniques easy to grasp, easy to integrate with other software tools, and easy to deploy.
GATE (a General Architecture for Text Engineering—see http://gate.ac.uk/) is an experimental apparatus, R&D platform and software suite with very wide impact in society and industry. There are many examples of applications: the UK National Archive uses it to provide sophisticated search mechanisms over its .gov.uk holdings; Oracle includes it in its semantics offering; Garlik Ltd. uses it to mine the web for data that might lead to identity theft; Innovantage uses it in intelligent recruiting products; Fizzback uses it for customer feedback analysis; the British Library uses it for environmental science literature indexing; the Stationery Office for value-added services on top of their legal databases. It has been adopted as a fundamental piece of web infrastructure by major organisations like the BBC, Euromoney and the Press Association, enabling them to integrate huge volumes of data with up-to-the-minute currency at an affordable cost, delivering cost savings and new products.
The EPP Project identifies criterial features for second language acquisition. It has engaged stakeholders in the teaching and testing of language learners. This is facilitated by the EPP network and website. The project has enabled Cambridge Assessment to define the English language constructs underlying Cambridge examinations at different proficiency levels more explicitly. The work has improved the tests themselves, but also allowed Cambridge Assessment to better communicate the qualities of their tests for accreditation and recognition. Stakeholders are more actively engaged through provision of resources for teachers, testers, ministries of education etc., on the website, and in seminars. The project has led to further research with an international language school, which has led to teachers and parents of the school pupils being more aware of the needs for successful second language acquisition.
Based in the School of English, the Research and Development Unit for English Studies (RDUES) conducts research in the field of corpus linguistics and develops innovative software tools to allow a wide range of external audiences to locate, annotate and use electronic data more effectively. This case study details work carried out by the RDUES team (Matt Gee, Andrew Kehoe, Antoinette Renouf) in building large-scale corpora of web texts, from which examples of language use have been extracted, analysed, and presented in a form suitable for teaching and research across and beyond HE, including collaboration with commercial partners.
Extracting information and meaning from natural language text is central to a wide variety of computer applications, ranging from social media opinion mining to the processing of patient health-care records. Sentic Computing, pioneered at the University of Stirling, underpins a unique set of related tools for incorporating emotion and sentiment analysis in natural language processing. These tools are being employed in commercial products, with performance improvements of up to 20% being reported in accuracy of textual analysis, matching or even exceeding human performance (Zoral Labs). Current applications include social media monitoring as part of a web content management system (Sitekit Solutions Ltd), personal photo management systems (HP Labs India) and patient opinion mining (Patient Opinion Ltd). Impact has also been achieved through direct collaboration with other commercial partners such as Microsoft Research Asia, TrustPilot and Abies Ltd. Moreover, international organisations such as the Brain Sciences Foundation and the A*Star Institute for High Performance Computing have realised major impact by drawing upon our research.
The research of Professor Paul Simpson and Dr Joan Rahilly has informed and enhanced the broader awareness and understanding of English language in the context of secondary level education in Northern Ireland, and has had particular influence on both clinical and developmental assessment of language use. The end users who have benefited from this research include (i) schools, colleges and lifelong learning, (ii) health and well-being agencies, and (iii) voluntary organisations and charities. The main achievements can be summarised as:
Biak (West Papua, Indonesia) is an endangered language with no previously established orthography. Dalrymple and Mofu's ESRC-supported project created the first on-line database of digital audio and video Biak texts with linguistically analysed transcriptions and translations (one of the first ever for an endangered language), making these materials available for future generations and aiding the sustainability of the language. Biak school-children can now use educational materials, including dictionaries, based on project resources. The project also trained local researchers in best practice in language documentation, enabling others to replicate these methods and empowering local communities to save their own endangered languages.
The Statistical Cybermetrics Research Group (SCRG) has developed social science sentiment analysis methods that estimate the strength of positive and negative sentiment in short informal social web text. These methods are encapsulated in the SentiStrength software, which is sold commercially, used commercially to develop socially useful computing applications (e.g., question answering systems, customer relations management systems), used to engage the public in science-related entertaining events, and used for data journalism to inform the public about specific news events. The research includes the development and evaluation of new sentiment analysis techniques that can detect informal expressions of sentiment in social web texts and that can detect the strength of positive and negative sentiment and not just its polarity. The research also includes the development of commercially viable software that includes the sentiment analysis methods.
The research has economic impact by enhancing the performance of commercial software systems, benefitting the owners of these systems (e.g., Yahoo!, Inbenta, Gemius, New Cities Foundation). The research also has economic impact by enhancing the customer relations of companies using sentiment-enhanced customer relations management systems, and with the traffic congestion detection system helping people to get to work on time. It has wide public services impact by helping people to find answers to their questions (via Yahoo! Answers). It has societal impact by supporting newsworthy analyses of social phenomena for the media. It has enhanced cultural life by driving spectacular lightshows during the London Olympics.