Web monitoring solutions for Sentiment Analysis and Brand Reputation

The KMS (Knowledge Mining System) platform offers an advanced tool to perform semantic analysis of unstructured data such as Web site, social media, database, to support information search and classification. The platform leverages conceptual analysis features to identify simply and complex semantic expressions, determine the sentiment and measure the Web reputation of a given brand.

Text Mining and Semantics provide the right response to Information Overload issues resulting from information management activities. Text Mining and Semantics help manage a wide range of texts automatically, by classifying them according to thematic categories and by extracting the most relevant information from them. Text Mining methodologies involve Linguistic and Statistical Analysis.

Linguistic Analysis is used to process the morphological, syntactic, logic-functional and semantic structure of a text and to identify its key elements. Firstly, morpho-syntactic analysis classifies each word from a grammatical point of view, so as to reduce the number of concepts describing a text. For instance, in a text concerning politics or business proper names of people, places and organizations can be used to easily identify a specific thematic category, while adjectives in an e-mail or a blog message can indicate whether a product or a service is positively or negatively evaluated. Secondly, logic-functional analysis helps identify who is doing what, how, when and where. Finally, semantic analysis interprets the underlying meaning of each single word. Through appropriate data projections, it is possible to assess with an excellent approximation the customer satisfaction level in relation to specific business initiatives or campaigns. If a company name or brand is placed in the “word space” and assessed against criteria such as “good”, “beautiful”, “young” and “reassuring”, you will be able to discover the real attitude of actual or potential users towards the products or services offered by that company or brand (Semiometry and Brand Analysis).

Statistic Analysis is used to assign documents both to predefined and customized thematic categories (Categorization) and to classification schemes which are not known in advance (Clustering). In the case of Categorization, an article can automatically be associated to thematic categories such as politics, business, sports or arts, while an e-mail message can automatically be redirected to the relevant company department. In the case of Clustering, texts are classified through spontaneous aggregation. For instance, claims and suggestions related to a company’s products and services are aggregated in various ways, so that the company can take advantage of new and original perspectives and trends.