Repustate's sentiment analysis API is powered by Turkish natural language processing (NLP). It analyzes Turkish data natively, without the need to translate any document into English, thus, giving more accurate and meticulously useful insights.
Repustate's Turkish sentiment analysis solution is made dedicatedly for the Turkish-speaking world. The tool can be used to analyze data from any Turkish source such as news, social media, blogs, reviews, and surveys.
The solution has its own dedicated Turkish part-of-speech tagger, Turkish lemmatizer, and Turkish-specific sentiment models. It also understands colloquial words and industry jargon. Turkish 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 Turkish sentiment analysis in action
What are the benefits of Repustate's Turkish Sentiment Analytics Tool?
The Repustate Turkish Sentiment Analysis solution is made specifically for Turkish 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 Turkish 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 Turkish natural language processing for the best results.
Turkish Text: We never translate. Repustate has unique speech taggers and sentiment models made just for Turkish 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.
Turkish Language Sentiment Models
Repustate has developed sentiment language models specific to Turkish
to capture the various phrases, idioms, and expressions that help define certain sentiments. It turns unstructured
Turkish data into business intelligence you can use to increase your value proposition, brand experience, and value delivery.
Take a quick tour of Repustate's Turkish text analytics solution
What are the Basic Steps in Turkish Sentiment Analysis?
Repustate has a massive corpus of Turkish text that has been tagged manually,
as the first step towards Turkish 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 Turkish text.
Feed this text into an ML-based algorithm to create an Turkish part-of-speech tagger.
Granulate the algorithm for deeper accuracy using NER.
Extract the sentiment score for each aspect, theme, and topic.
Repustate uses Turkish Named Entity Recognition (NER) with
advanced semantic search to identify brand and business entities in data. No matter how misspelled a word is,
the Turkish 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 Turkish sentiment analysis?
Trying to achieve Turkish sentiment analysis by using an API that uses translations can
yield incorrect results. So, the answer is, no. As your Turkish sentiment analysis company,
Repustate, uses intricate Turkish 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 Turkish NLP in Sentiment Analysis Tools
Repustate's Turkish 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 Turkish 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 Turkish 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 Turkish sentiment analysis uncover your hidden insights
Real-World Applications of Turkish Text Sentiment Analysis
Repustates's Turkish sentiment analysis API is made for the Turkish language and its dialects.
Powered by Turkish 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 Turkish
sentiment analysis to organizations in various industries.
A Ankara-based healthcare corporation wants to
understand the doctor-patient relationship to make the
whole system more sensitive towards healthcare, Repustate's
Turkish 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 Ankara-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 Istanbul-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 Turkish sentiment analysis tool provides them with a highly-precise,
customized, stock sentiment analysis solution powered by Turkish 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 Antalya 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 Turkish sentiment analysis API helps them understand their data. By applying
Turkish 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.
Turkish Enterprise Search
Repustate's Enterprise Search automatically annotates
your Turkish 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 Turkish Enterprise Search.
Bütün diller aynı değildir
Dil bilgisi kuralları bir dilden diğerine değişir. Fiil çekimi, isim-fiil uygunluğu ve olumsuzluk kuralları dilden dile değişir.
Türkçe benzersiz bir dildir ve bir dizi yolla İngilizce'den farklıdır. Türkçe duygu analizi yaparken İngilizce duygu analizlerindeki aynı teknikleri ve dil modellerini kullanmak korkunç derecede yanlış sonuçlar doğuracaktır.
Bu yüzden Repustate Türkçe geliştirildi - , konuşma etiketleyicisi bir kimsenin bir Türkçe bölümü dahil, bir Türkçe lemmatizer ve tabi ki Türkçe - özel duygu modelleri.
İşte bu yüzden Repustate, Türkçe bir sözdizimsel analiz, Türkçe bir lemmatizer ve tabii ki Türkçeye özel duygusal modeller dahil Türkçedeki duygu analizlerine yardım etmek için Türkçeye özel araçlar geliştirdi.
Türkçe sözdizimsel analiz
Türkçe sözdizimsel analiz, Repustate'in bir metin bloğu içinde duygunun nerede olabileceği üzerine yoğunlaşmasına izin verir. Fiiller, isimler ve sıfatlar, duyguyu belirlemek için gerekli ipuçlarını sağlamaktadır.
Hızlı ve doğru Türkçe sözdizimsel analiz oluşturulması için elle etiketlenmiş büyük bir bütünce Türkçe metne sahip olmanız gerekir. Bu Türkçe metin daha sonra Türkçe sözdizimsel analiz oluşturmak için bir makine öğrenme algoritmasına beslenilir.
Bütünce ne kadar büyük olursa, ve daha da önemlisi ne kadar çeşitli olursa, Türkçe sözdizimsel analiz oluşturmada da o kadar iyi sonuçlar olur. Repustate iyi kapsama alanını garantilemek için çeşitli kaynaklardan gelen verileri kaparak büyük bir Türkçe metin bütüncesi yarattı.
Türkçe dil duygu modelleri
Repustate, Türkçe yazarken duygu tanımlanmasına yardımcı olan çeşitli ifadeler, deyimler ve anlatımlar yakalamak için Türkçeye özgü duygu dil modelleri geliştirmiştir. Türkçe dilini benzersiz ve İngilizceden çok farklı kılan çeşitli dil bilgisel yönlerini anlamak, Repustate'in Türkçe duygu analizini kendisi kadar hızlı ve doğru olmasına olanak sağlayan şeydir.