Repustate's sentiment analysis API is powered by Danish natural language processing (NLP). It analyzes Danish data natively, without the need to translate any document into English, thus, giving more accurate and meticulously useful insights.
Repustate's Danish sentiment analysis solution is made dedicatedly for the Danish-speaking world. The tool can be used to analyze data from any Danish source such as news, social media, blogs, reviews, and surveys.
The solution has its own dedicated Danish part-of-speech tagger, Danish lemmatizer, and Danish-specific sentiment models. It also understands colloquial words and industry jargon. Danish 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.
See Repustate's Danish sentiment analysis in action
What are the benefits of Repustate's Danish Sentiment Analytics Tool?
The Repustate Danish Sentiment Analysis solution is made specifically for Danish data. It is highly
customizable and can be calibrated to be an exact fit for your business. Listed below are the main advantages of the tool:
Obtain granular Danish sentiment analysis by aspect
Data security with on-premise deployment or through Cloud
Custom-made model that can be specific to your brand and industry domain
Multilingual sentiment analysis capability to help you scale globally fast
Why Choose Repustate Over Others?
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.
Premium Support: As our client, you will have a dedicated engineer assigned to your account.
Technology: We apply artificial intelligence and machine learning to Danish natural language processing for the best results.
Danish Text: We never translate. Repustate has unique speech taggers and sentiment models made just for Danish text analysis. In fact, each of our 23 languages has an ML model based on the natural language natively.
Accuracy: Our aspect-driven approach to sentiment is granular, accurate, and targeted.
Speed: Our API can process 1,000 comments per second.
Customizable: We custom-build the model to capture your most important aspects and topics.
Scale: Our API can easily scale from 1 to 10 million to 100 million documents and beyond.
Integration: The Repustate solution integrates seamlessly with your existing technology. You do not need 3rd party support for any underlying technology.
Competition: Our model is the most accurate in NER compared to the competition that includes Google, Amazon, and Microsoft.
Check out our comparison.
Deployment Flexibility: We offer both, a Cloud model, and an on-premise installation for data security, in a one-click solution.
No Hidden Fees: Our pricing includes support, updates, training, and deployment.
Iterative: Our models get more and more intelligent with training and as they process more data.
Danish Language Sentiment Models
Repustate has developed sentiment language models specific to Danish
to capture the various phrases, idioms, and expressions that help define certain sentiments. It turns unstructured
Danish data into business intelligence you can use to increase your value proposition, brand experience, and value delivery.
Take a quick tour of Repustate's Danish text analytics solution
What are the Basic Steps in Danish Sentiment Analysis?
Repustate has a massive corpus of Danish text that has been tagged manually,
as the first step towards Danish 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:
Collect a massive, highly varied corpus (collection of texts) of the manually tagged Danish text.
Feed this text into an ML-based algorithm to create an Danish part-of-speech tagger.
Granulate the algorithm for deeper accuracy using NER.
Extract the sentiment score for each aspect, theme, and topic.
Repustate uses Danish Named Entity Recognition (NER) with
advanced semantic search to identify brand and business entities in data. No matter how misspelled a word is,
the Danish 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.
Should translations be used for Danish sentiment analysis?
Trying to achieve Danish sentiment analysis by using an API that uses translations can
yield incorrect results. So, the answer is, no. As your Danish sentiment analysis company,
Repustate, uses intricate Danish 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.
Applications of Danish NLP in Sentiment Analysis Tools
Repustate's Danish 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.
Analyze news - text, audio & video:
Sentiment analysis from news streams is really easy with Repustate's Sentiment Analysis API.
Whether you want Danish 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.
Analyze surveys, forums, and Google reviews:
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 Danish Voice of Customer analysis
helps you make sense of all that data.
Understand public sentiment:
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
Let Repustate's Danish sentiment analysis uncover your hidden insights
Real-World Applications of Danish Text Sentiment Analysis
Repustates's Danish sentiment analysis API is made for the Danish language and its dialects.
Powered by Danish 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 Danish
sentiment analysis to organizations in various industries.
A Aarhus-based healthcare corporation wants to
understand the doctor-patient relationship to make the
whole system more sensitive towards healthcare, Repustate's
Danish 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 Aarhus-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 Copenhagen-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 Danish sentiment analysis tool provides them with a highly-precise,
customized, stock sentiment analysis solution powered by Danish 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 Odense 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 Danish sentiment analysis API helps them understand their data. By applying
Danish 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.
Danish Enterprise Search
Repustate's Enterprise Search automatically annotates
your Danish 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 Danish Enterprise Search.
Ikke alle sprog er ens
Grammatiske regler varierer fra sprog til sprog. Reglerne for hvordan udsagnsord bøjes, om de bøjes efter person og hvordan negationer fungerer varierer fra sprog til sprog.
Dansk er et unikt sprog, og det adskiller sig fra engelsk på en række forskellige måder. At bruge de samme teknikker og sproglige modeller, der fungerer for engelsksprogede sentimentanalyser, til at foretage dansksprogede sentimentanalyser ville føre til komplet fejlagtige resultater.
Det er netop derfor, at Repustate har udviklet værktøjer specifikt til det danske sprog, der hjælper med sentimentanalyser på dansk, inklusiv en dansk ordklasse-tagger, en dansk lemmatiseringsfunktion og naturligvis sentimentmodeller udviklet særligt til dansk.
Den danske ordklasse-tagger gør det muligt for Repustate at bestemme mere nøjagtigt, hvor sentimenter ligger i en blok af tekst. Udsagnsord, navneord og tillægsord giver os de nødvendige signaler til at bestemme sentimentet.
For at lave en hurtigt og nøjagtig dansk ordklasse-tagger, kræves et enormt korpus af dansk tekst, der er blevet tagget manuelt. Denne danske tekst kan så bruges til at 'fodre' en maskinlæringsalgoritme, der skaber en dansk ordklasse-tagger.
Desto større korpusset er og - endnu vigtigere - desto mere varieret, desto bedre bliver resultatet, når man udvikler en dansk ordklasse-tagger. Repustate har samlet et enormt korpus af dansk tekst med data, der er hentet fra en række forskellige kilder for at sikre bred dækning.
Repustate har udviklet sproglige sentimentmodeller særligt til dansk for at finde de forskellige vendinger, talemåder og udtryk, der er med til at definere sentimentet, når man skriver på dansk. Det er forståelsen for de forskellige aspekter af dansk grammatik, der gør det til et sprog, som er unikt og klart adskiller sig fra engelsk, der gør Repustates dansksprogede sentimentanalyse så hurtig og nøjagtig, som den er.