Open-Source Natural Language Processing and Computational Archival Science

Transcription

1 Open-Source Natural Language Processing and Computational Archival Science Kalina Bontcheva University of The University of Sheffield, This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivs Licence

2 Automatic Metadata Enrichment Use Natural Language Processing, e.g. Information Extraction recognise names of people, organisations, locations, dates, references, etc. Linking to LOD knowledge resources Term recognition identify domain-specific terms Extend automatically document metadata, to improve search quality Derive aggregate statistics and visualisations

3 GATE Widely used open source NLP framework Version 8.5 recently released Development led by The University of Sheffield Funded by EU and UK research grants, and commercial funders Around downloads per version

4 GATE open source Research Take Up LGPL licensing + easy SaaS use Linguistics, humanities, journalism, etc. Community Many core contributors Plugins from around the world Friendly user groups Training Annual GATE training course Bespoke online and on-site training POC Consulting

5 GATE open-source social media tools Name/Description Description / Domain License GATE Numerous tools for text analytics, LGPL + including social media plugin specific TwitIE NER for tweets LGPL GATECloud Various cloud-based GATE services, including social media analytics SaaS model Sentiment analysis Generic twitter-based sentiment analysis LGPL Tweet Collector Social media analytics SaaS model YODIE Cloud-based named entity disambiguation and linking; version for social media SaaS model

6 GATE Annotation

7 Term recognition

8 Traditional keyword search: Example

9 Person search: Example

10 Organizations: Example (1)

11 Organizations: Example (2)

12 Semantic Search UI: Example

13 Finding Topical Clusters (DCMS docs) Fake news, social media, political, online, information, accounts, disinformation, social platforms, misinformation, bots People, US, information, data, Facebook, right, companies Facebook, advertising, ads, Google, UK, political UK, EU, US, fact, companies, internet, law, media, protection, Facebook Data, Alexander Nix, Cambridge Analytica, Facebook, SCL, Aleksandr Kogan, Christopher Wylie, etc. Arron Banks (VoteLeave campaign), EU, Cambridge Analytica, data, UKIP, referendum, Trump, Mississippi, campaigners

14 Real-time Visual Analytics

15 Live Analysing the Brexit Vote

16 ONLINE ABUSE, MISINFORMATION Abuse quantity and proportion increased between the two elections Males, Paper conservatives received more abuse published at ICWSM Misinformation in UK EU membership referendum 2016 Post-truth politics: " 350 million" figure widely shared, false Propaganda and fake news: state-owned propaganda sites and fake news sites widely shared, mostly by leavers Partisan media: role of the hyper-partisan sites

17 Links for more info GATE at GateCloud at Brexit Visualisations at Brexit study blog post from NESTA at Brexit study blog posts from Sheffield at UK elections monitor at

18 Acknowledgements This work supported by: the European Union/EU under the Information and Communication Technologies (ICT) theme of the 7th Framework and H2020 Programmes for R&D KNOWMAK (726992) DecarboNet (610829) Pheme (611233) SoBigData (654024) COMRADES (687847) OpenMinted (654021) Kconnect (644753) Nesta