I am co-organizing an LREC workshop on Language Engineering for Online Reputation Management.
The LREC 2012 workshop on Language Engineering for Online Reputation Management intends to bring together the Language Engineering community (including researchers and developers) with representatives from the Online Reputation Management industry, a fast-growing sector which poses challenging demands to text mining technologies. The goal is to establish a five-year roadmap on the topic, focusing on what language technologies are required to get there in terms of resources, algorithms and applications.
Online Reputation Management deals with the image that online media project about individuals and organizations. The growing relevance of social media and the speed at which facts and opinions travel in microblogging networks make online reputation an essential part of a company’s public relations.
While traditional reputation analysis was based mostly on manual analysis (clipping from media, surveys, etc.), the key value from online media comes from the ability of processing, understanding and aggregating potentially huge streams of facts and opinions about a company or individual. Information to be mined includes answers to questions such as: What is the general state of opinion about a company/individual in online media? What are its perceived strengths and weaknesses, as compared to its peers/competitors? How is the company positioned with respect to its strategic market? Can incoming threats to its reputation be detected early enough to be neutralized before they effectively affect reputation?
In this context, Natural Language Processing plays a key, enabling role, and we are already witnessing an unprecedented demand for text mining software in this area. Note that, while the area of opinion mining has made significant advances in the last few years, most tangible progress has been focused on products. However, mining and understanding opinions about companies and individuals is, in general, a much harder and less understood problem.
The aim of this workshop is to bring together the Language Engineering community (including researchers and developers) with representatives from the Online Reputation Management industry, with the ultimate goal of establishing a five-year roadmap on the topic, and a description of the language technologies required to get there in terms of resources, algorithms and applications.
With this purpose in mind, the workshop will welcome both research papers and position statements from industry and academia. The agenda for the event will include both presentations (from accepted submissions and selected invited speakers) and a collaborative discussion to sketch a roadmap for Language Engineering in Online Reputation Management. The EU project Limosine (starting November 2011) will be used as a funding instrument to ensure that participation is representative and key players are engaged in the workshop. The workshop is held in coordination with the RepLab initiative, a CLEF 2012 evaluation initiative for systems dealing with Online Reputation Management challenges.