Repustate draws insights directly from any native Russian text to give you in-depth, actionable data analysis with one click.
Get Your Free TrialRepustate's sentiment analysis API is powered by Russian natural language processing (NLP). It analyzes Russian data natively, without the need to translate any document into English, thus, giving more accurate and meticulously useful insights.
Repustate's Russian sentiment analysis solution is made dedicatedly for the Russian-speaking world. The tool can be used to analyze data from any Russian source such as news, social media, blogs, reviews, and surveys.
The solution has its own dedicated Russian part-of-speech tagger, Russian lemmatizer, and Russian-specific sentiment models. It also understands colloquial words and industry jargon. Russian natural language processing, coupled with named entity recognition (NER), helps it identify topics and themes in the data for more granular sentiment analysis, leading to key business insights.
The Repustate Russian Sentiment Analysis solution is made specifically for Russian customizable and can be calibrated to be an exact fit for your business. Listed below are the main advantages of the tool:
The Repustate model has the highest accuracy in NER compared to other tools. It is not an off-the-shelf product, but a highly personalized, scalable solution with dedicated customer support. Here is why our clients worldwide (NA, EMEA and Asia Pacific) collaborate with us.
Repustate has developed sentiment language models specific to Russian to capture the various phrases, idioms, and expressions that help define certain sentiments. It turns unstructured Russian data into business intelligence you can use to increase your value proposition, brand experience, and value delivery.
Repustate has a massive corpus of Russian text that has been tagged manually, as the first step towards Russian sentiment analysis. This corpus is then processed by an ML model for high precision in aggregate sentiment scoring. The steps can be laid out as:
Repustate uses Russian Named Entity Recognition (NER) with advanced semantic search to identify brand and business entities in data. No matter how misspelled a word is, the Russian NLP model will reproduce the name in the native script and give accurate name search, transliteration, and identity verification measures. This gives high-accuracy ranked results, based on the linguistic, phonetic, and specific cultural variation patterns of the names.
Trying to achieve Russian sentiment analysis by using an API that uses translations can yield incorrect results. So, the answer is, no. As your Russian sentiment analysis company, Repustate, uses intricate Russian NLP for higher accuracy in sentiment scoring of your data. This is because translations dilute the nuance of a statement. If a text has multiple topics, sentiments, and themes, as reviews and comments usually do, the aggregate semantic score of the data (+1 for positive, and -1 for negative) will be inaccurate with translations.
Repustate's Russian sentiment analysis API helps you get useful insights through Social media listening from Facebook, Twitter, Instagram, and even video-based platforms like TikTok and YouTube. This is very useful to brands who want to capture sentiments around specific facets of their business, product line, or service.
Sentiment analysis from news streams is really easy with Repustate's Sentiment Analysis API. Whether you want Russian NLP analysis for employee surveys or product reviews, our tool gives you relevant insights. Furthermore, its visualization dashboard converts the data into charts, graphs, and tables, so you can understand the data easily.
Companies dedicate a large number of resources to understanding their customers by running feedback campaigns in their stores, social forums, mobile apps, and websites. Repustate's Russian Voice of Customer analysis helps you make sense of all that data.
From policy decisions to bad customer service, whatever the issue may be, people share this information with the world. This data can be vital to a government body, or a company looking to improve its brand perception and market share.
Repustates's Russian sentiment analysis API is made for the Russian language and its dialects. Powered by Russian NLP, the solution gives you accurate and fast insights through aspect based sentiment analysis of your data. Here are some real-world examples of how Repustate has provided Russian sentiment analysis to organizations in various industries.
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 API can enable them to semantically identify various aspects related to doctor-patient interaction and sentiment related to those aspects. With Repustate, this St. Petersburg-based healthcare system can unlock the advanced applications of NLP in Healthcare and have the answers they've been searching for in half the time it would have taken before.
A Moscow-based financial corporation realizes that it's not good for business if they are unable to monitor global financial and stock market news accurately and fast. Since even names of companies change when the news is in a foreign language, the company realizes it is missing out on vital information in an industry that thrives on quick decision-making. Repustate's Russian sentiment analysis tool provides them with a highly-precise, customized, stock sentiment analysis solution powered by Russian NLP. Our sentiment analysis solution gives them insights into market sentiment based on price movements of securities traded, as well as financial news coverage in all major languages. They also leverage the real-time dashboard that shows market sentiment scores and share prices for different debt instruments and equities in an easy-to-understand format.
A public transport agency from Kazan wants to improve its service and brand perception and approach Repustate with the problem. They want to provide better service by addressing negative feedback and restructuring resources. They want to have an authentic and detailed understanding of the sentiment of daily commuters using public modes of transport. Repustate's Russian sentiment analysis API helps them understand their data. By applying Russian natural language processing techniques to all the reviews and comments gathered from public forums, Repustate's solution is able to give them useful insights they can use to achieve their goals.
Repustate's Enterprise Search automatically annotates your Russian data with semantic information. This includes relevant entities, topics, and entity-specific metadata. You can search all metadata associated with any given entity that Repustate finds 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.