Sentiment analysis, stemming and lemmatization, partofspeech tagging and chunking, phrase extraction and named entity recognition.
Text Classification, Article Summarization, Sentiment Analysis, Stock symbol extraction, Person Names Extractor, Language Detection, Locations Extractor, Adult content Analyzer.
Returns the sentiment of Tweets. Two online APIs call the Twitter API to analyze Tweets from a given Twitter user or Tweets returned by a Twitter search query. The offline API analyzes texts of Tweets you’ve already got, one Tweet at a time.
The WebKnox text processing API lets you process (natural) language texts. You can detect the text’s language, the quality of the writing, find entity mentions, tag partofspeech, extract dates, extract locations, or determine the sentiment of the text.
API is designed to turn any text into constituent terms (meaningful expressions), entities (names of people, place and things), and sentiment terms. Languages supported are English, Spanish, French, German, Chinese, Swedish, Greek, Czech, Italian and Russian.
Cloud based Natural Language Processing API. Includes Sentiment and Language Detection.
Sentiment Analysis Spanish
Sentiment analysis for Spanish language of any given tweet.
provides advanced cloudbased and onpremise text analysis infrastructure that eliminates the expense and difficulty of integrating natural language processing systems into your application, service, or data processing pipeline.
Text processing framework to analyse Natural Language. It is especially focused on text classification and sentiment analysis of online news media (generalpurpose, multiple topics).
Yactraq is a cloud service that converts audiovisual content into topic metadata via speech recognition & natural language processing. Customers use Yactraq metadata to target ads, build UX features like content search/discovery and mine Youtube videos for brand sentiment. In the past such services have been expensive and only used by large video publishers. The unique thing about Yactraq is we deliver our service at a price any product developer can afford.
Bitext Sentiment Analysis
The purpose of this service is to extract opinions from text. An opinion represents the subject an author is writing about and a sentiment score that classifies how positively or negatively the author feels towards that subject. Deep Linguistic Analysis is used to identify the subject the author is discussing.
Textalytics Sentiment Analysis
Multilingual sentiment analysis of texts from different sources (blogs, social networks etc). Besides polarity at sentence and global level, 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 userdefined entities and concepts, making the service a flexible tool applicable to any kind of scenario.
This tool works by examining individual words and short sequences of words (ngrams) and comparing them with a probability model. The probability model is built on a prelabeled test set of IMDb movie reviews. It can also detect negations in phrases, i.e, the phrase -not bad- will be classified as positive despite having two individual words with a negative sentiment.
Starget sentiment analysis
This is a short text (a twitt or a single sentence) sentiment classification API. It has two types of analysis: one for finding more (but less accurate) sentiment snippets and another one for finding more accurate sentiment (but missing some difficult cases).
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.
Free Natural Language Processing Service
100% free service including sentiment analysis, content extraction, and language detection. Enjoy!