Fast, accurate Arabic sentiment analysis. No translations needed.

Why Choose Repustate Over Others?

Repustate is the preferred Arabic sentiment analysis company because our sentiment analyzer 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 in the Middle East and the Arabic-speaking world collaborate with us.

1. Premium Support: As our client, you will have a dedicated engineer assigned to your account.
2. Technology: We apply artificial intelligence and machine learning to Arabic natural language processing for the best opinion analysis results.
3. Arabic Text: We never translate. Repustate has unique Arabic part-of-speech taggers and sentiment models made just for Arabic text analysis. In fact, each of our 23 languages has an ML model based on the natural language natively.
4. Accuracy: Our aspect-driven approach to sentiment is granular, accurate, and targeted.
5. Speed: Our API can process 1,000 comments per second.
6. Customizable: We custom-build the model to capture your most important aspects and topics.
7. Scale: Our API can easily scale from 1 to 10 million to 100 million documents and beyond.
8. Integration: The Repustate solution integrates seamlessly with your existing technology. You do not need 3rd party support for any underlying technology.
9. Competition: Our model is the most accurate in NER compared to the competition that includes Google, Amazon, and Microsoft. Check out our comparison.
10. Deployment Flexibility: We offer both, a Cloud model, and an on-premise installation for data security, in a one-click solution.
11. No Hidden Fees: Our pricing includes support, updates, training, and deployment.
12. Iterative: Our models get more and more intelligent with training and as they process more data.

Arabic Language Sentiment Models

Repustate has developed sentiment language models specific to Arabic to capture the various phrases, idioms, and expressions that help define certain sentiments. It turns unstructured Arabic data into business intelligence you can use to increase your value proposition, brand experience, and value delivery.

What are the Steps in Arabic Sentiment Analysis?

We collate a massive corpus of Arabic text, which is manually tagged and processed by an ML model for high precision in aggregate sentiment scoring. The steps can be defined as follow:

Repustate uses Arabic Named Entity Recognition (NER) to identify brand and business entities in data. No matter how misspelled a word is, our Arabic 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.

Why should we never use translations for Arabic Sentiment Analysis?

Translations yield incorrect results to a very high degree since they dilute the nuance of the word in the original language. Different languages have different grammatical constructs for negations, amplifiers, and root words. If a text has multiple topics and sentiments (as reviews and comments usually do) this difference in language rules renders the aggregate sentiment score of the data wrong. Therefore, translations can lead to incorrect insights that can be detrimental to a company’s return on investment and business.

As your Arabic sentiment analysis company, Repustate never translates your data. We use our own painstakingly collated, highly precise, individually developed Arabic part-of-speech tagger and lemmatizers. This is what ensures you the highest possible accuracy of sentiment scores from your data, so you can get the right insights.