We’ve all heard of sentiment analysis, but what exactly is it and what can it do for your brand, your business, and how can you get started with it?
This paper presents a new unsupervised approach to generating ultra-concise summaries of opinions. We formulate the problem of generating such a micropinion summary as an optimization problem, where we seek a set of concise and non-redundant phrases that are readable and represent key opinions in text. We measure representativeness based on a modified mutual information function and model readability with an n-gram language model.
This is a short study paper that categorizes positive and negative review sentences into 4 categories: positive only, praise, negative only and complaint. The intuition is that praise sentences and complaints tend to be more informative than plain positive only or negative only sentences. This paper thus tries to understand the properties of such text that we consider as complaints and praises.
In this paper we describe our mining system which automatically mines tags from feedback text in an eCommerce scenario. It renders these tags in a visually appealing manner. Further, emoticons are attached to mined tags to add sentiment to the visual aspect.
Opinion Driven Decision Support System (ODSS) refers to the use of large amounts of online opinions to facilitate business and consumer decision making. The idea is to combine the strengths of search technologies with opinion mining and analysis tools to provide a synergistic decision making platform. The research and engineering problems related to developing such …
The Opinosis Summarizer Software is a demo version of a summarizer that generates concise abstractive summaries of highly redundant text. It was primarily used to summarize opinions, and thus it can be regarded as a opinion summarization software. However, since the underlying approach is general and assumes no domain knowledge, with a few minor tweaks …