1. Kickoff Meeting Opinion profile construction from Social Media. A case study of restaurant reviews Funded By Cogito Foundation Hatem Ghorbel ISIC-HE-Arc Ingénierie Martin Hilpert UniNe

2. Outline of the talk —Objectives —Research plan —Planning —Work of Mehdi Davary —Yelp Academic Data

3. Objectives-1- Our goal is to analyze restaurant reviews in terms of semantic frames in order to provide an opinion profile that reflects customer satisfaction along several dimensions.

4. Objectives-2- Our research output will consist of a tool capable of extracting fine grained opinion profiles for the restaurants that are reviewed in our data and summarizing the result to the final user.

5. Example of reviews

6. Research Plan 1.Data acquisition and description 2.Qualitative analysis 3.Automatic feature extraction 4.Polarity measure 5.Web Demonstration 6.Evaluation and dissemination

7. Data acquisition and description Yelp’s Academic Dataset, a collection of restaurant reviews in the online city guide Yelp (http://www.yelp.com, data to be obtained)http://www.yelp.com See Davary’s talk

8. Qualitative analysis Construction of a ‘restaurant frame’ that contains the dimensions that matter to restaurant reviewers. friendliness and speed of the staff, the taste and freshness of the food, and the ease of access, a restaurant is quiet or busy, romantic or rustic, modern or traditional, Establishment of a lexicon of words for each variable

9. WP2 delivrables The outcome of this task is a lexicon database describing the restaurant frame.

10. Automatic restaurant feature extraction The construction of an algorithm that probabilistically classifies each sentence according to its topic We end up with separate databases of sentences about food quality, service, ambience, accessibility, and other dimensions described in the constructed lexical database. (LDA)

11. WP3 delivrables The outcome of this task is a restaurant opinion profile construction tool.

12. Polarity measure The polarity measure of each entry of such opinion profiles for the restaurants. Utilize and extend the list of Hu and Liu [Hu2004], which comprises 6800 words that define for each entry a positive or negative polarity.

13. WP4 delivrables The outcome of this task is a polarity measure module integrated to the opinion profile construction tool.

14. Web Demonstration Make accessible in a web interface opinion profiles for all reviewed restaurants that make it easy for customers to find a restaurant of a specific profile. A teacher who is planning a school outing might be looking for a restaurant that is easy to access, affordable, and good in service, even though the food is mediocre.

15. WP5 delivrables A web interface demonstrating the capability of the opinion profile construction tool applied to the restaurant reviews stored in our dataset.

16. Evaluation Compare the opinion profiles of 10 restaurants constructed by our tool to manual construction over a sample of 50 comments. Metrics : recall and precision Compare with the baseline defined in the state of the art of the field.

17. Dissemination The tool will be freely accessible as a web site to the interested community Conference publications The site will also be diffused to the public at large, customers and businesses alike. Serve as a proof of concept that can be transferred to other domains.

18. Planning