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Fast, accurate Arabic sentiment analysis. No translations needed.

Repustate draws insights directly from any native Arabic text to give you in-depth, actionable data analysis with one click.

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Arabic Sentiment Analysis

Document Level Sentiment Analysis

Repustate’s AI-driven Arabic sentiment analysis automatically identifies any positive or negative sentiment in your text.

ذهبوا الى المطعم الجديد الليلة الماضية واحبو المشروبات، خاصتا القهوة العربية، لكن الطعام كان سيء. السمك المشوي كان مندي وكان كاليماري مطاطيًا

Language: Arabic

Entities: مطعم, طعام, مشروب, قهوة عربية, السمك المشوي, كاليماري

Sentiment: Negative

Semantic Understanding In Native Language

And because it’s trained natively and doesn’t require translations, Repustate understands local sayings, idioms, and slang

Phrase/Idiom Meaning
العرق يمد لسابع جد الآباء والأبناء يشبهون بعضهم البعض
ضَرْبَة مِعَلِّم عمل جيد
سَمْن عَلَى عَسَل متوافقة تماما
اِسْتَعْرَض عَضَلاتُه إظهار القوة
قد الدنيا الافضل عالميا
Our native machine learning models combine all the factors of prior polarity, lemmatization, grammatical constructs with dialects, idioms, puns, emojis etc - without any translations

Topic & Aspect Based Sentiment Analysis

Repustate can even apply aspect-based sentiment analysis to your Arabic text and create a richer and more in-depth analysis of your data.

ذهبوا الى المطعم الجديد الليلة الماضية واحبو المشروبات، خاصتا القهوة العربية، لكن الطعام كان سيء. السمك المشوي كان مندي وكان كاليماري مطاطيًا
Aspect Topic Sentiment
مشروبات قهوة عربية واحبو
طعام السمك المشوي مندي
طعام كاليماري مطاطيًا

See it in action

Select sample input


Language Arabic
Topic & Aspect Analysis
Aspect Topic Sentiment

Book a personalized 15-minute demo to learn more about Repustate's Arabic sentiment analysis

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Arabic Sentiment Analysis Dashboard

Repustate IQ: The only Arabic sentiment analysis dashboard you'll need

  • No translations: all analysis done natively in Arabic
  • No coding required: easy one-click upload of Arabic spreadsheets
  • Save time: accurate Arabic sentiment analysis available instantly
  • Actionable insights: automatic reporting with beautiful graphs and charts

Arabic Data Collection

Repustate can find the Arabic text most relevant to you no matter where it is on the public internet . Repustate can even extract valuable semantic insights from Arabic videos on sites like YouTube and TikTok. Have your own Arabic data? No problem - simply upload your data to Repustate and let our Arabic text analytics pipeline do the rest.

Take a quick tour of Repustate's Arabic text analytics solution

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What are the benefits of Repustate's Arabic NLP solution?

The Repustate Arabic Sentiment Analysis solution is made specifically for Arabic data. It understands three major Arabic dialects - Gulf Peninsular, Egyptian, and Levantine Arabic - and can be calibrated to be an exact fit for your business. Listed below are the main advantages of the tool:

  • Understand your Arabic-speaking customers
  • Evaluate the 3 largest and most popular Arabic dialects
  • Visualize all the insights in a customer insights dashboard
  • Obtain granular Arabic emotion analysis by aspect
  • Data security with on-premise deployment or through Cloud
  • Custom-made model specific to your brand, domain, and dialect
  • Multilingual semantic analysis capability to help you scale globally fast

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.

Interested in learning more about Repustate's Arabic sentiment analysis?

Book your demo today

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:

Step 1:

Collect a massive, highly varied corpus (collection of texts) of the manually tagged Arabic text.

Step 2:

Create an Arabic part-of-speech tagger.

Step 3:

Build lemmatization i.e. apply rules of conjugating nouns and verbs based on gender and tense.

Step 4:

Build prior polarity to determine the positive and negative context of a word.

Step 5:

Determine grammatical constructs to define negations and amplifiers.

Step 6:

Feed sentiment scores to train the model.

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.

Repustate has helped banks, governments and hotels extract business insights from their Arabic customer data. We can help you, too.

Find out how

Applications of Arabic NLP in Sentiment Analysis Tools

Analyze Twitter, Facebook, Insta, TikTok, & YouTube content:

Repustate's Arabic sentiment analysis API helps you get useful insights through Social media listening from Facebook, Twitter, Insta, 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 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 Arabic Voice of Customer analysis helps you make sense of all that data.

Analyze news - text, audio & video:

Emotion analysis from news streams is really easy with an Arabic sentiment analysis company like Repustate. Whether you want an Arabic NLP solution 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.

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 market share.

Applications of Arabic Text Sentiment Analysis

Repustates's Arabic sentiment analysis API is made for the Arabic language and its dialects. Powered by Arabic NLP, the solution gives you accurate and fast insights through Voice of Customer analysis of your data. Here are some real-world examples of how Repustate has helped organizations across industries in analyzing sentiment in Arabic.