Unlock the meaning in your Finnish data.

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

Your Finnish 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.

Should translations be used for Finnish sentiment analysis?

Finnish 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 Finnish sentiment analysis would yield terribly inaccurate results.

Repustate Sentiment Analysis

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

What are the basic steps in Finnish sentiment analysis?

Finnish part-of-speech tagging allows us 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 Finnish part-of-speech tagger, data scientists have to have a massive corpus of manually tagged Finnish text. This Finnish text can then be fed into a machine-learning algorithm to create an Finnish part-of-speech tagger.

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

Taking it a step further, by using Finnish 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

Finnish language sentiment models

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

Applications of Text-based Sentiment Analysis in Finnish

Our Finnish semantic analysis API is optimized to understand and analyze your data in standard Finnish 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. Let`s take a look at a few applications:

A Tampere based healthcare corporation wants to understand the doctor-patient relationship to make the whole system more sensitive towards healthcare, Repustate’s Finnish 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 Tampere 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 Helsinki 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 Utrecht 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.

Finnish Enterprise Search

Repustate's Enterprise Search automatically annotates your Finnish 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 Finnish Enterprise Search.

Kaikki kielet eivät ole samanlaisia

Kielioppisäännöt vaihtelevat kielestä toiseen. Verbin taivutuksen, substantiivin ja verbin kongruenssin sekä negaation säännöt ovat erilaisia kielestä riippuen.

Suomi on ainutlaatuinen kieli, joka eroaa englannista monin tavoin. Englannin tunneanalyysin tekniikoiden ja kielimallien käyttäminen suomenkielisessä mielipideanalyysissä johtaisi kammottaviin epätarkkuuksiin.

Tämän vuoksi Repustate onkin kehittänyt suomelle sopivia työkaluja suomenkielistä mielipideanalyysiä auttamaan; niihin lukeutuvat muun muassa puheseuraimen suomenkielinen osa, suomen perusmuotoistaja sekä tietysti suomelle sopivia mielipidemalleja.

Puheseuraimen suomenkielinen osa

Puheseuraimen suomenkielisen osan avulla Repustate kykenee tarkentamaan mielipiteen sijainnin tekstipätkissä. Verbit, substantiivit ja adjektiivit antavat mielipiteen varmentamiseen tarvittavia johtolankoja.

Puheseuraimen nopean ja tarkan suomenkielisen osan luomiseen vaaditaan massiivinen manuaalisesti merkityn suomenkielisen tekstin korpus. Tämä suomenkielinen teksti voidaan syöttää koneoppimisalgoritmiin, joka luo puheseuraimen suomenkielisen osan.

Mitä suurempi ja laaja-alaisempi korpus, sitä parempia puheseuraimen suomenkielisen osuuden luonnissa saadaan. Repustate on luonut valtavan suomenkielisen korpuksen hakemalla dataa useista eri lähteistä, mikä varmistaa laajan kattavuuden.

Suomen mielipidemallit

Repustate on kehittänyt erityisesti suomelle sopivia mielipidemalleja, joiden avulla voidaan tunnistaa suomenkielessä mielipidettä ilmaisevia kielikuvia ja ilmaisuja. Repostaten suomenkielinen mielipideanalyysin tarkkuus ja nopeus johtuvatkin juuri suomen ainutlaatuisten, englannista poikkeavien kieliopillisten piirteiden tunnistamisesta.