o Abstract—The paper discusses on the ongoing work of editorial analysis and synthesis construction, basically text annotation and the linguistic criteria for distinguishing between facts and opinions. Further we also talk on the factors playing a crucial role in determining the strengths of opinions. We also discuss on the process of argumentation structure outlining, a major part of our work that directs the analysis of opinions in the discourse level. I. INTRODUCTION ITH the increasing interest of the general public towards socio-political happenings, it is a growing practice these days to read and analyze the different opinions on a particular event published by the media in the form of editorials. Such an analysis would not only help to understand how a particular event has been perceived by different media sources but also provide a relatively true view of the happenings and hence is of primary interest to journalists, public figures and political analysts. The online electronic resource http://www.nepalmonitor.com for instance, includes the editorials from different national and international newspapers organized on a monthly basis. These editorials basically talk on some of the prime events that have taken place in Nepal in a particular month. The editorial sources in the link provided above range from Voice of America, The Japan Times, The Washington Times, The New Nation – Bangladesh, Dawn, Gulf News – UAE, The Himalayan Times, The Kathmandu Post, The Hindu – India, Times of India , The Indian Express and Economic Times – India. It is indeed interesting to see how these editorials differ in opinions, how convincing or persuasive the arguments appear in providing supports to certain conclusion(s) and if possible judge the different degrees of biases and prejudices evident in them. These problems are quite difficult even to humans, let alone the machine. From an automation perspective, it would have been a good thing if there were a provision for constructing a synthesis of the different opinionated arguments (Positive, Negative and Neutral) in one document with some useful information like (source, date, orientation etc. of the editorial) clearly mentioned so that the readers need not Manuscript received August 8,2009 B. Krishna Bal is with the Madan Puraskar Pustakalaya, Lalitpur, Patan Dhoka, Nepal (phone: 977-1-5521393; fax: 977-1-5536390; e-mail: bal@ mpp.org.np). P. Saint Dizier is with IRIT, 118 Narbonne 31062 Toulouse, France. (e-mail: stdizier@irit.fr). unnecessarily have to go through all of them, yet get a vivid picture of the happenings or events. Even better would have been the case, if there were a mechanism to track changes in opinion across editorials over a common topic with time. The proposed work aims to build a framework and more precisely a computational linguistic model that would suggest appropriate techniques and methods for analyzing the editorials and constructing a synthesis. At the moment, we have basically identified the different linguistic components and are in the process of working towards specifying the different underlying computational procedures required for the model. The organization of the paper is as follows. In section I, we introduce our problem, state the research aims and briefly talk about the current status of the work. In section II, we shed light on Opinion Mining and discuss on the different sub problems under the larger problem. We also correlate the association of these sub problems with our problem of editorial analysis and synthesis. In section III, we give an overview of the related works and also throw light on the novelties that our work carries. Moving on to section IV, we discuss on the linguistic basis for distinguishing facts and opinions. In section V, we talk on the linguistic aspects for determining the strength of opinions. Similarly in section VI, we throw light on one of the crucial components of our research work – outlining the argumentation structure of editorials (support and rhetorical relations). We also briefly discuss on the semantic tagset employed for the purpose of annotation. In section VII, we report our ongoing works on editorials collection and annotation. II. OPINION MINING AS A PROBLEM Although Opinion Mining has emerged only quite recently as a subdiscipline under computational linguistics, a considerable amount of work has already been done in this direction. These works range from a variety of task domains like mining the product reviews available on the web, sentiment classification of documents, opinion mining and summarization to much more. Irrespective of the nature of different specific tasks, Opinion Mining generally encompasses the following generic problems: 1. Determining the subjectivity or identifying the subjective and objective expressions in texts [1, 2, 7]. 2. Determining the orientation or polarity of the subjective expressions [3, 4, 5, 6, 11]. 3. Determining the strength of the orientation of the subjective expressions [8]. This involves deciding Who Speaks for Whom? Towards Analyzing Opinions in News Editorials Bal Krishna Bal and Patrick Saint-Dizier W