Unlock the meaning in your Russian data.

Our AI-driven Russian sentiment API determines the sentiment in your Russian text. All analysis is done natively in Russian, no translations are used leading to greater accuracy.

Your Russian Sentiment Analysis Company

The Challenge

Not all languages are the same; grammar rules vary from one language to another and the rules of verb conjugation, noun-verb agreement, and negations vary from one language to another. This can make it extremely difficult to gauge text analytics without the proper tools in place to understand the nuances of other languages.

Russian is a unique language and it differs from English in a number of ways: from sentence structure to words and phrases that may be used differently, using the same techniques and language models that work for English sentiment analysis when conducting Russian sentiment analysis would yield terribly inaccurate results.

Repustate Sentiment Analysis

Because of the challenges for applying high-level sentiment analysis for Russian companies, Repustate has developed Russian-specific tools to decipher words, industry jargon, and the feelings behind your customer's words. Russian sentiment analysis, including an Russian part of speech tagger, an Russian lemmatizer, and of course, Russian-specific sentiment models.

Russian sentiment analysis: How we do it

Russian part-of-speech tagging allows Repustate to narrow in on where the sentiments may lie within a block of text. Verbs, nouns, and adjectives provide the cues necessary to determine sentiment and aid in detailed analysis. In order to create a fast and accurate Russian part-of-speech tagger, leaders have to have a massive corpus of manually tagged Russian text. This Russian text can then be fed into a machine-learning algorithm to create an Russian part-of-speech tagger.

The larger the corpus, and more importantly, the more varied the corpus, the better the results in creating the Russian part-of-speech tagger. Repustate has created a massive corpus of Russian text grabbing data from a variety of sources to ensure good coverage.

Taking it a step further, by using Russian Named Entity Recognition with the advanced semantic search for enterprises, we can identify brand and business entities in data. No matter how misspelled a word is, our API will reproduce the first name in native script and thus improve the accuracy of name searching, transliteration, and the grade of identity verification initiatives. This gives high accuracy ranked results, on the basis of the linguistic, phonetic, and specific cultural variation patterns of the names

Russian language sentiment models

Repustate has developed sentiment language models specific to Russian to capture the various phrases, idioms, and expressions that help define sentiment when writing in Russian. Understanding the various grammatical aspects of the Russian language that make it unique and very different from English is what allows Repustate's Russian sentiment analysis to be as fast and as accurate as it is.

Applications of Text-based Sentiment Analysis in Russian

Our Russian semantic analysis API is optimized to understand and analyze your data in standard Russian language and dialects. Our API can be used to analyze the public sentiment about a product, service, government policy opinions, stock market trends, and social media listening.

For example, if a St. Petersburg based healthcare corporation wants to understand the doctor-patient relationship to make the whole system more sensitive towards healthcare, Repustate’s Russian sentiment analysis can enable them to semantically identify various aspects related to doctor-patient interaction and sentiment related to those aspects. With Repustate’s sentiment and text analytics, this St. Petersburg based healthcare system can have the answers they’ve been searching for in half the time it would have taken before.

To take a step further, let's take an example of a Moscow based finance corporation that deals in the forex market and monitors on International market news to tap into market trends. Repustate’s forex sentiment analysis unleashes a whole new arena for growth opportunities for the corporation by projecting and alerting them with semantically driven trends in the market.

Finally, let’s take a look at how the Kazan based Government agency benefits from sentiment analysis. As a public transport agency, it would like to understand the sentiment of daily commuters using public modes of transportation. Repustate’s sentiment analysis can find the hidden sentiment through social media channels and social forums and understand user opinion about the service to decide what they need to update in their system to have happy customers.

Russian Enterprise Search

Repustate’s Enterprise Search automatically annotates your Russian data with semantic information. This includes relevant entities, topics, and entity-specific metadata. Search any and all metadata associated with any given entity that Repustate finds. You can search by market cap or industry type for business, or perform your search by nationality. Over 100 metadata properties can be searched, and all of them can be automatically determined by Repustate’s Russian Enterprise Search.