Textalytics Media Analysis API analyzes mentions, topics, opinions and facts in all types of media. This API provides services for: - Sentiment analysis - Extracts positive and negative opinions according to the context. - Entities extraction - Identifies persons, companies, brands, products, etc. and provides a canonical form that unifies different mentions (IBM, International Business Machines Corporation, etc.) - Topic and keyword extraction - Facts and other key information - Dates, URLs, addresses, user names, e-mails and money amounts. - Thematic classification - Organize information by topic using IPTC standard classification (more than 200 categories hierarchically structured). - Configured for different type of media: microblogging and social networks, blogs and news - All features available in Spanish and English
Textalytics Topics Extraction tags locations, people, companies, dates and many other elements appearing in a text written in Spanish, English, French, Italian, Portuguese or Catalan. This detection process is carried out by combining a number of complex natural language processing techniques that allow to obtain morphological, syntactic and semantic analyses of a text and use them to identify different types of significant elements. The elements identified are classified according to the following predefined categories: named entities (people, organizations, places, etc.), concepts (significant keywords in the text), time expressions, money expressions, URIs, phone number expressions, alphanumeric patterns, quotations, relations [beta]. Remember, all this functionality in a multilingual environment.
Automatic multilingual text classification according to pre-established categories defined in a model. The algorithm used combines statistic classification with rule-based filtering, which allows to obtain a high degree of precision for very different environments. Three models available: IPTC (International Press Telecommunications Council standard), EuroVocs and Corporate Reputation model. Languages covered are Spanish, English, French, Italian, Portuguese and Catalan.
Multilingual sentiment analysis of texts from different sources (blogs, social networks,...). Besides polarity at sentence and global level, Textalytics Sentiment Analysis 1.1 uses advanced natural language processing techniques to also detect the polarity associated to both entities and concepts in the text. Sentiment Analysis also gives the user the possibility of detecting the polarity of user-defined entities and concepts, making the service a flexible tool applicable to any kind of scenario. Additionally, Sentiment Analysis detects if the text processed is subjective or objective and if it contains irony marks [beta], both at global and sentence level, giving the user additional information about the reliability of the polarity obtained from the sentiment analysis.
Automatic language detection for texts obtained from any kind of source (blog, twitter, online news and so on). Through statistic techniques based on N-grams evaluation, more than 60 languages are correctly identified.
This service provides detailed linguistic information for a given text in English, Spanish, French, Italian, Portuguese and Catalan. There are three operating modes that cover different aspects of the morphosyntactic and semantic analysis: Lemmatization: provides the lemmas of the different words in a text; PoS tagging: provides not only the grammatical category of a word, but also all the possible grammatical categories in which a word of each specific PoS type can be classified (check the tagset associated https://textalytics.com/core/tagset); Syntactic analysis: provides a thorough syntactic analysis, giving a complete syntactic tree where the leaves represent the most basic elements and their morphological and semantic analyses.
This service connects extracted entities and concepts to related semantic linked data. The main source of external information used is DBpedia, which provides structured data extracted from Wikipedia (check the DBpedia Data Set to read more on how this is done). Through a specific identifier, a number of attributes associated to an element are returned in the language specified by the user, allowing to expand the information already extracted through other Textalytics' services (such as Topics Extraction or Lemmatization, POS and Parsing).
A service for automatic proofreading of multilingual texts. This API uses multilingual Natural Language Processing technology to check the spelling, grammar and style of your texts with high accuracy, in order to provide precise and up-to-date suggestions and educational explanations based on references. The current supported languages are Spanish, English, French and Italian.
User Demographics allows to extract some important demographics (type, gender, age) for a given social media user. Multilingual models are available including English, Spanish, French and Italian, among others. State-of-the-art information extraction and text classification technology are used to guess those facts from his/her login, name and profile description.
Textalytics - Meaning as a Service The easiest way to embed semantic analysis into your applications Textalytics is a set of semantic APIs which allow to incorporate capabilities for extracting meaning from multilingual content in various industries and application scenarios, in a simple and efficient way. Textalytics include: - Media Analysis API: for brand monitoring, competitive analysis and sentiment detection in both social and traditional media. - Semantic Publishing API: for content tagging and enrichment and text proofreading in media and content publishers. - Core API: a set of APIs providing granular, customizable functionality.