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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.
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:
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 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.
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:
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.
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.
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.
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.
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.
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 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.
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.
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.