News
“EU Researchers Saw it Coming” – Research*eu Magazine
Following the United Kingdom’s decision to leave the European Union on 23 June 2016, the EU-funded SENSEI project has revealed that it accurately predicted the result of the referendum by analysing 6 million social media conversations in the weeks preceding the vote. The SENSEI (Making Sense of Human-Human Conversation Data) project aims to make sense of the millions of blog posts and social media conversations that take place every day… >> Read the entire article ...
read moreLondon: Media/Text Analytics Customer Event
On 19/09/2016 a dissemination event called “Language Technology Meets Social Media Conversation in the News” (see: www.meetup.com/textanalytics/events/233885011/) was held in central London at the British Computer Society. Invited were media professionals from various media organisations/media units across the UK and, in addition, members of the London Text Analytics meet up group. The event was organised by USFD and UESSEX (Kruschwitz). Presentations were made by project members from USFD (Gaizauskas, Hepple, Foster) and...
read moreSENSEI @ “E-Commerce Customer Experience”
The Sensei team has participated in the international “E Commerce Customer Experience” in September in Paris, an event with over 500 companies, 4 specialized exhibition areas and a Start-Up Village. The Sensei industrial partner Teleperformance had a booth dedicated to the Sensei Project, and Hugo Zaragoza (Websays) and Vincenzo Giliberti (Teleperformance) held a very successful workshop on “Social Media + Machine Learning = A new Customer Care Experience. The Sensei Project.”. >> Event...
read moreSENSEI predicts Brexit Outcome
Monitoring Brexit – The Story In the month preceding the referendum date, SENSEI’s system monitored millions of social media conversations to predict the outcome of the referendum. Every day, more than 300 000 posts across multilingual media sources on the topic of the UK EU Referendum are captured and automatically analysed by the SENSEI technology. Most exit polls were showing confidence the REMAIN side would prevail. In contrast, the SENSEI system hit with very high accuracy the final outcome. ...
read moreSENSEI live at Radio 24
Interview (Italian) at Radio 24 (Italian Radio) about SENSEI monitoring Brexit Referendum Go to the Radio webpage or listen it here http://www.sensei-conversation.eu/wp-content/uploads/2016/06/160622-smart-city.mp3 ...
read moreMonitoring the Brexit Campaign
SENSEI started to monitor the Brexit Campaign. Find it at www.sense-eu.info Press Release here
read moreUNITN scores high at CoNLL 2016 Shared Task
SENSEI-UNITN team ranked 3rd at the CoNLL 2016 Shared Task on Shallow Discourse Parsing in the end-to-end parsing and 1st in the argument extraction sub-task. The SENSEI team participated to the CoNLL 2016 Shared Task on Shallow Discourse Parsing on end-to-end parsing of English news. Discourse parsing has utility for many other NLP tasks such as summarization and opinion mining. Penn Discourse Treebank style discourse parsing is a composite task of detecting explicit and non-explicit discourse relations, their connective and...
read moreSENSEI Overview Paper Published on Lecture Notes in Artificial Intelligence, 2016
Read the full paper here
read moreSENSEI-LIF team Ranked 2nd at the Semeval sentiment analysis
The SENSEI team participated to the Semeval scientific evaluation campaign, under the sentiment analysis track 4.A (polarity detection in tweets). Polarity detection consists in detecting whether the author expressed a positive or negative sentiment in a text. This task is a basic building block for analysing social media conversations. The system developed by SENSEI consists in a family of convolutional neural networks (CNNs) trained from multiple views of the input, and combined with a deep neural network. The different views are...
read morePapers Accepted at LREC 2016
Following papers have been accepted at LREC 2016: Celli F., Riccardi G. and Alam F., “Multilevel Annotation of Agreement and Disagreement in Italian News Blogs”, Proc. LREC, Portroz, 2016. Chowdhury S., Stepanov A. E. and Riccardi G., “Transfer of Corpus-Specific Dialogue Act Annotation to ISO Standard: Is it worth it ?”, Proc. LREC, Portroz, 2016. Danieli M., Balamurali A. R., Stepanov A. E., Favre B., Bechet F. and Riccardi G., “Summarizing Behaviors: An Experiment on the Annotation of...
read more
