Repustate's sentiment analysis API is powered by
Japanese natural language processing (NLP). It analyzes Japanese data natively,
without the need to translate any document into English, thus, giving more accurate
and meticulously useful insights.
Repustate's Japanese sentiment analysis
solution is made dedicatedly for the Japanese-speaking world. The tool can be used
to analyze data from any Japanese source such as news, social media, blogs, reviews,
The solution has its own dedicated Japanese
part-of-speech tagger, Japanese lemmatizer, and Japanese-specific sentiment
models. It also understands colloquial words and industry jargon. Japanese 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
See Repustate's Japanese sentiment analysis in action
What are the benefits of Repustate's Japanese Sentiment Analytics
The Repustate Japanese Sentiment Analysis solution is made specifically for Japanese
customizable and can be calibrated to be an exact fit for your business. Listed below
are the main advantages of the tool:
Obtain granular Japanese 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
Technology: We apply artificial intelligence and machine learning to Japanese
natural language processing for the best results.
Japanese Text: We never translate. Repustate has unique speech taggers and
sentiment models made just for Japanese 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
Speed: Our API can process 1,000 comments per second.
Customizable: We custom-build the model to capture your most important aspects and
Scale: Our API can easily scale from 1 to 10 million to 100 million documents and
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.
Japanese Language Sentiment Models
Repustate has developed sentiment language
models specific to Japanese
to capture the various phrases, idioms, and expressions that help define certain
sentiments. It turns unstructured
Japanese data into business intelligence you can use to increase your value
proposition, brand experience, and value delivery.
Take a quick tour of Repustate's Japanese text analytics solution
What are the Basic Steps in Japanese Sentiment Analysis?
Repustate has a massive corpus of Japanese text that has been tagged manually,
as the first step towards Japanese 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 Japanese text.
Feed this text into an ML-based algorithm to create an Japanese part-of-speech
Granulate the algorithm for deeper accuracy using NER.
Extract the sentiment score for each aspect, theme, and topic.
Repustate uses Japanese Named Entity
Recognition (NER) with
advanced semantic search to identify brand and business entities in data. No matter
how misspelled a word is,
the Japanese 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 Japanese sentiment analysis?
Trying to achieve Japanese sentiment analysis by using an API that uses
yield incorrect results. So, the answer is, no. As your Japanese sentiment
Repustate, uses intricate Japanese NLP for higher accuracy in sentiment scoring of
This is because translations dilute the nuance of a statement. If a text has
sentiments, and themes, as reviews and comments usually do, the aggregate semantic
of the data (+1 for positive, and -1 for negative) will be inaccurate with
Applications of Japanese NLP in Sentiment Analysis
Repustate's Japanese sentiment analysis API helps you get useful insights through
Social media listening
from Facebook, Twitter, Instagram, and even video-based platforms like TikTok and
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
Whether you want Japanese NLP analysis for employee surveys or product reviews, our
you relevant insights. Furthermore, its visualization dashboard converts the data into
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 Japanese Voice of Customer
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 Japanese sentiment analysis uncover your hidden insights
Real-World Applications of Japanese Text Sentiment Analysis
Repustates's Japanese sentiment analysis API is made for the Japanese language and
Powered by Japanese 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 Japanese
sentiment analysis to organizations in various industries.
A Osaka-based healthcare corporation wants to
understand the doctor-patient relationship to make the
whole system more sensitive towards healthcare, Repustate's
Japanese 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 Osaka-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 Tokyo-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.
names of companies change when the news is in a foreign language, the company realizes
missing out on vital information in an industry that thrives on quick decision-making.
Repustate's Japanese sentiment analysis tool provides them with a highly-precise,
customized, stock sentiment analysis solution powered by Japanese NLP.
Our sentiment analysis solution gives them insights
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 Kyoto wants to improve its service and brand
and approach Repustate with the problem. They want to provide better service by
negative feedback and restructuring resources. They want to have an authentic and
understanding of the sentiment of daily commuters using public modes of transport.
Repustate's Japanese sentiment analysis API helps them understand their data. By
Japanese natural language processing techniques to all the reviews and comments
from public forums, Repustate's solution is able to give them useful insights they can
to achieve their goals.
Japanese Enterprise Search
Repustate's Enterprise Search automatically annotates
your Japanese data with semantic information. This includes relevant entities,
entity-specific metadata. You can search all metadata associated with any given entity
Repustate finds by market cap or industry type for business, or perform your search by
Over 100 metadata properties can be searched, and all of them can be automatically
by Repustate's Japanese Enterprise Search.