Sentiment analysis

Sentiment Detection (including sentiment analysis, English for " mood detection" ) is a sub- field of text mining is the automatic analysis of texts with the aim of identifying a stance expressed as positive or negative.

Introduction

People converse in natural languages ​​, ie languages ​​that convey ambiguous and not only structurally the importance and information other than formal languages ​​and their automatic processing by computer is difficult. Computational linguistics explores how you can still analyze natural language with computers. For a long time it was hoped thereby to the artificial intelligence, which seeks to create intelligent systems, but since even modern computers are still far from this goal, the objectives of the speech processing, rejection is a strong and turned simpler but more promising methods. Such a goal is to work out specific knowledge from texts, such as the subject or - as here - the setting of the author on the subject. The area, which deals with the solution of such tasks is called text mining, based on data mining, with which it has the basic ideas together. The methods by which the sentiment detection works, come from areas such as statistics, machine learning and natural language processing.

Procedure

The task of sentiment detection is addressed by statistical methods. Moreover, one can include the grammar of the surveyed utterances. For statistical analysis, one starts from a basic set of concepts (or n-grams ), which is associated positive or negative trends. The frequencies of positive and negative terms in the analyzed text are compared with each other and determine the presumed attitude.

Based on machine learning algorithms can be applied. On the basis of pre-processed parts, which are known to the attitudes, such algorithms can also learn more terms for which trend they refer.

Using techniques of Natural language processings can knowledge of the natural language part of the decision. For example, the grammar of texts analyzed machine learned patterns can be applied to the structure.