Repustate's sentiment analysis API is
powered by Norwegian natural language processing (NLP). It analyzes Norwegian
data natively, without the need to translate any document into English,
thus, giving more accurate and meticulously useful insights.
Repustate's Norwegian sentiment
analysis solution is made dedicatedly for the Norwegian-speaking world. The
tool can be used to analyze data from any Norwegian source such as news,
social media, blogs, reviews, and surveys.
The solution has its own dedicated Norwegian
part-of-speech tagger, Norwegian lemmatizer, and Norwegian-specific
sentiment models. It also understands colloquial words and
industry jargon. Norwegian 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 Norwegian sentiment analysis in action
What are the benefits of Repustate's Norwegian Sentiment
The Repustate Norwegian Sentiment Analysis solution is made specifically
for Norwegian 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 Norwegian 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
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 Norwegian
natural language processing for the best results.
Norwegian Text: We never translate. Repustate has unique speech taggers
and sentiment models made just for Norwegian text analysis. In fact,
each of our 23 languages has an ML model based on the natural language
Accuracy: Our aspect-driven approach to sentiment is granular, accurate,
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
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
Iterative: Our models get more and more intelligent with training and as
they process more data.
Norwegian Language Sentiment Models
Repustate has developed sentiment
language models specific to Norwegian
to capture the various phrases, idioms, and expressions that help define
certain sentiments. It turns unstructured
Norwegian data into business intelligence you can use to increase your
value proposition, brand experience, and value delivery.
Take a quick tour of Repustate's Norwegian text analytics solution
What are the Basic Steps in Norwegian Sentiment Analysis?
Repustate has a massive corpus of Norwegian text that has been tagged
as the first step towards Norwegian sentiment analysis. This corpus is then
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 Norwegian text.
Feed this text into an ML-based algorithm to create an Norwegian
Granulate the algorithm for deeper accuracy using NER.
Extract the sentiment score for each aspect, theme, and topic.
Repustate uses Norwegian Named Entity Recognition
advanced semantic search to identify brand and business entities in data. No
matter how misspelled a word is,
the Norwegian 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 Norwegian sentiment analysis?
Trying to achieve Norwegian sentiment analysis by using an API that
uses translations can
yield incorrect results. So, the answer is, no. As your Norwegian
sentiment analysis company,
Repustate, uses intricate Norwegian 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 Norwegian NLP in
Sentiment Analysis Tools
Repustate's Norwegian sentiment analysis API helps you get useful
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
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 Norwegian 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 Norwegian 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
be, people share this information with the world. This data can be
a government body, or a company looking to improve its brand
Let Repustate's Norwegian sentiment analysis uncover your
Real-World Applications of Norwegian Text Sentiment
Repustates's Norwegian sentiment analysis API is made for the Norwegian
language and its dialects.
Powered by Norwegian NLP, the solution gives you accurate and fast
of your data. Here are some real-world examples of how Repustate has
sentiment analysis to organizations in various industries.
A Trondheim-based healthcare corporation wants to
understand the doctor-patient relationship to make the
whole system more sensitive towards healthcare, Repustate's
Norwegian 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 Trondheim-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 Oslo-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
Repustate's Norwegian sentiment analysis tool provides them with a
customized, stock sentiment analysis solution powered by Norwegian
Our sentiment analysis
solution gives them insights into
market sentiment based on price movements of securities traded, as
financial news coverage in all major languages. They also leverage
real-time dashboard that shows market sentiment scores and share
different debt instruments and equities in an easy-to-understand
A public transport agency from Bergen 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
Repustate's Norwegian sentiment analysis API helps them understand
their data. By applying
Norwegian 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.
Norwegian Enterprise Search
Search automatically annotates
your Norwegian 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
by Repustate's Norwegian Enterprise Search.
Alle språk er ikke like
Grammatikkreglene varierer mellom ulike språk. Regler for negasjoner, bøying av verb og samsvar mellom substantiv og verb varierer fra det ene språket til det andre.
Norsk er et unikt språk og skiller seg fra engelsk på en rekke ulike måter. Hvis man hadde gjort sentimentsanalyse på norsk ved å bruke de samme teknikkene og språkmodellene som fungerer på sentimentsanalyse på engelsk, ville det medført forferdelig unøyaktige resultater.
Derfor har Repustate utviklet verktøy spesielt for det norske språk. De kan brukes til sentimentsanalyse på norsk, inkludert merking av ordklasser på norsk, norsk lemmatisering og selvsagt spesifikke sentimentsmodeller for norsk.
Merking av ordklasser på norsk
Merking av ordklasser på norsk lar Repustate fastslå hvor i en tekstblokk sentimentet kan befinne seg. Verb, substantiver og adjektiver gir de nødvendige ledetrådene for å avgjøre sentimentet.
For å merke norske ordklasser raskt og nøyaktig må du ha en massiv samling med manuelt merket tekst på norsk. Denne norske teksten mates deretter inn i en maskinlæringsalgoritme for å skape en funksjon som kan merke norske ordklasser.
Jo større tekstsamlingen er, og enda viktigere, jo mer variert den er, jo bedre resultater gir den norske ordklassemerkingen. Repustate har satt sammen en massiv samling med norsk tekst og sørget for at grunnlaget er bredt og variert, ved å hente data fra en rekke ulike kilder.
Sentimentsmodeller for det norske språk
Repustate har utviklet sentimentsmodeller spesielt for det norske språk. De fanger opp diverse fraser, uttrykk og idiomer som bidrar til å definere sentimentet når man skriver på norsk. Forståelse for de ulike grammatiske aspektene som gjør det norske språket unikt og svært forskjellig fra engelsk, er det som gjør Repustates norske sentimentsanalyse så rask og nøyaktig som den er.