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Tecnología de semántica profunda para analizar opiniones en redes sociales

Resumen

Tipo:
Oferta Tecnológica
Referencia:
TOCZ20141107001
Publicado:
01/12/2014
Caducidad:
01/12/2015
Resumen:
Un equipo de investigación de una universidad checa especializado en análisis de opiniones ha desarrollado una tecnología para analizar opiniones en redes sociales. Esta tecnología ayuda a monitorizar de forma comprensible las discusiones de redes sociales y detecta los temas más importantes y las opiniones relevantes en cada tema. La tecnología utiliza semántica profunda para identificar una estructura de árbol de los principales temas relacionados con una entidad específica. Cada tema se describe por palabras clave o comentarios más importantes. Se buscan compañías especializadas en ofrecer servicios de monitorización de redes sociales para establecer acuerdos de licencia.

Details

Tittle:
Deep semantic technology for analyzing opinions in social media
Summary:
A Czech university research team aimed at sentiment analysis has developed a technology for analyzing opinions in social media. The technology helps to comprehensibly monitor social media discussions. It detects the most important topics and the key opinions within each topic. The university research team is interested in license agreement with companies engaged in delivering social media monitoring services to highly discussed brands in social media.
Description:
Sentiment analysis (also opinion mining) is a kind of natural language processing for tracking the mood of the public about a particular product or topic. It is very important tool for marketers. It can help them to evaluate the success of new product or campaign launch or identify which version of product or service is popular. Current social media monitoring technologies express mass opinions only through sentiment polarity figures (positive, neutral, negative) and word clouds. Therefore gathered information does not allow enough flexible and competent reaction.

Czech researchers have developed new technology for prioritizing content in social media conversations. The technology uses deep semantics to identify a tree structure of the main topics related to a specified entity. Each topic is described either by keywords or the most important comments. Prioritizing feature enable to understand the main discussed issues quickly. It can compare the topic structures of different entities or different periods of the same entity. It can also identify what are the unique topics for the specified entity or period. Developed technology is statistical and it can be easily adapted to other languages.
Advantages and Innovations:
Deep semantic technology enables to answer the crowd sentiment question by text. The key opinions are placed within a hierarchy of discussed topics. It provides competitive and temporal comparisons.

It is language-independent. It can be easily adapted to other languages.
Stage of Development:
Prototype available for demonstration
IPs:
Secret Know-how
CommeR Statunts Regarding IPR Status:
Software license

Partner sought

Type and Role of Partner Sought:
Companies engaged in delivering social media monitoring services to highly discussed brands in social media.

Task to be performed by the partner sought: License agreement.

Client

Type and Size of Client:
University
Already Engaged in Trans-National Cooperation:
Si
Languages Spoken:
English

Keywords

Technology Keywords:
01005003 Contenidos digitales, publicidad electrónica
11003 Sociedad, información y medios