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The 4 Finest Text Analytics APIs For Movie Reviews

Sentiment/Opinion Analysis is the process that consists of considering data to gauge customers´ reviews. It is connected to opinion and emotion, judgement and feelings, which are assessed by means of NLP (Natural Language Processing) and ML (Machine Learning). With the aid of AI (Artificial Intelligence) that generates algorithms, you can get useful information for your organizations whether reviews are positive, negative or neutral.

We are now concerned specifically about movie reviews. By processing viewers´ feedback on movies they have seen, Text Analytics results from social media monitoring, brand monitoring, customer service and market research. The purpose is marketing, and the output will pulse the audience`s preferences, which are closely connected with the atmosphere in a particular social context.

Text Analytics APIs classify insights by segmenting social groups by age, gender, social status, and the movies by theme, category, language, settings, plot, acting, starring. The process contemplates feedback on social media sites, forums, blogs, and countless sources of text and audio data. The classification of data considers IMDB dataset, labelled reviews and Bags of Words (also called Bags of Popcorn for this category).

ZYLA Labs Sentiment Analysis API  and Text Analytics for movie reviews go deeper into the process and can detect how viewers have taken the movie regarding length, budget, direction. They monitor distribution of the length of reviews by a word count function (statistically negative reviews tend to be shorter than positive ones). Text is usually messy as people may use awkward punctuation and vocabulary to express themselves, even with spelling mistakes. This API maps characters and words to representative numbers by means of ML models. Non-alphabetic characters and stop-words (articles and prepositions) are removed to clear the text data up.

HULU API  is a popular sentiment analysis platform for video and on-demand services. It uses transformation of text to numbers and analysis of reviews by means of BoW. You get the glossary from the whole text dataset, and it applies BoW. An entry, sentence or line of text is defined to transform the text in a vector that consists of a frequency count. The reviews analyzed in this way give the client an accurate feedback of the movie.

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Movie Database (IMDB Alternative) has Access to movie and TV information in a similar way as IMDB. It analyzes on the basis of title, year, meta-score rating, IMDB rating, date of release, runtime, genre, direction, scriptwriters, starring, plot, awards, posters, and so on and so forth. Its output deserves a thumb up for its accuracy and immediateness.

UTELLY API  searches reviews on a universal basis and analyzes text data. This API recommends movies, series and TV shows on the different streaming services, and builds recommendation considering target audiences. It provides also a report on availability on platforms, year of release, ratings, etc. It also has a Data Match Endpoint to load your title details and match them to IVA`s database.

These are the foundations. There is more to offer, like the use of bigrams (sequence of two words) so as to obtain more contextual meaning. Text Analytics  and Opinion Analysis APIs distinguish true positive rate from false positive rate, and their functionality is so ample to cover all eventual requirements, needs and purposes. For one thing, no film producer, director and staff can ignore the relevance of Text Analytics APIs for movie reviews.

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