EMOTIVE

The ability for ordinary people to express and exchange their opinions and feelings has increased beyond all expectations in the past ten years of internet expansion and availability. To the military and national security agencies this has provided both opportunities and challenges. Opportunities have emerged in the sense of readily available awareness of discontent and oppositional movements and initiatives. Recent urban disturbances have illustrated the key role played by social networks in the fast-moving events of Summer 2011. The challenges have escalated due to the sheer number of sources of social interaction and public communication media. This research addresses some of these issues in a bold initiative to combine well established and considered science with the increasingly familiar tools of Web 2.0.

The Concept

Four of the most popular sources of the public exchange of ideas (email, social networks, such as Facebook, microblogs, such as Twitter and comments to newspaper editorials and high-profile stories) will be selectively monitored. These kinds of texts are relatively sparse, grammatically incorrect, informal and largely very different from classical NLP texts. Due to this it was suggested that a new NLP pipeline is necessary to deal with sparse texts of a highly informal nature.

Sensitive words and phrases which may be of concern to the military and national security agencies and especially emotionally charged words and phrases are extracted by extending a Natural Language Processing technique already developed for email by the Principal Investigator. The team has developed an ontology (a rule-based linguistic database) in which the extracted words and phrases can be semantically filtered and restricted to a manageable set of agreed terms. The ontology is trained to recognise the words and phrases, make semantic links between them and deliver one or more accepted descriptors to the analysts. EMOTIVE monitors the traffic of sensitive words and phrases filtered through the ontology when applied to specific incidents, individuals and groups.

Uses

It can be argued that the general public will be direct beneficiaries of this research in that the defence and national security agencies who act as guardians of public safety and order will be further equipped by this tool to identify, evaluate and ultimately safeguard the public from potentially harmful events. Defence and national agencies will already be experienced at monitoring these data sources but this tool adds an extra filter of analysis, it will work in almost real time, will amalgamate data from several sources if desired and will provide harmonised output.

Benefits

Technical details of the teams’ work on the novel ontology and natural language processing based linguistic analysis system for monitoring and extracting fine-grained emotions from sparse social media content, such as Twitter messages. Instead of classifying sentiment based on polarity (a well researched problem), the work considers Ekman’s basic cross cultural emotions and extracts emotions at a more fine grained level than existing approaches, achieving a very high F-measure (commonly used to evaluate these types of systems), that is currently the best reported for this task.

The EMOTIVE project is funded by the EPSRC and DSTL and conducted at Loughborough University, within the Centre for Information Management in School of Business and Economics (formerly Information Science department). The researchers working on the project are Prof. Tom Jackson (Principal Investigator), Dr. Ann O’Brien (Co-Investigator), Dr. Martin Sykora (Research Associate), and Dr. Suzanne Elayan (Research Associate).

Route to Commercialisation

The Emotive Engine has a number of applications in fields such as marketing, social media and law enforcement.

Emotive can be built into a variety of software packages and platforms, from a simple app to a stand alone reporting suite.

The Emotive Engine is available under license from LU to developers and we are happy to work with end clients to develop their own systems incorporating the engine.

Please visit our website at :http://emotive.lboro.ac.uk/