What is Sentiment Analysis?
Sentiment Analysis (SA) addresses the problem of determining the objectivity or polarity of the input. The main parameters defining the scope of a SA method are the target language, domain and media type (traditional or social media).
By SA we refer to a polarity classification task in the Natural Language Processing (NLP) domain. Whereas the majority of approaches perform binary categorization of textual data into positive and negative classes, more advanced classification schemes also include mixed (both positive as well as negative) and neutral (neither positive nor negative) classes. In contrast to SA, the goal of subjectivity analysis is the detection of private states (opinions, emotions, sentiments, beliefs, speculations), classifying textual input as objective/subjective. The scope of a SA approach is mainly defined by three parameters – target language, domain and type of media (traditional or social media).
The high interest in ongoing researches in the field is motivated by its practical applications – in marketing, e.g. monitoring of public opinions or product reviews, political science, e.g. observation of public opinions during election campaigns, social science, economics, etc.
The objective of SentiSAIL is the realization of SA multilingually, both for traditional and social media. SentiSAIL is incorporated into the SAIL LABS Media Mining System (MMSys), which is a state-of-the-art Open-Source-Intelligence system, performing multifaceted processing of unstructured textual and speech data.
To learn more about Sentiment Analysis and the Sentiment Analysis capabilities and features in our Media Mining Client, download the related documentation by clicking on the button below.