ARABIC SENTIMENT ANALYSIS

Unlock the meaning in your Arabic data

Our AI-driven Arabic sentiment analysis API determines the sentiment in your Arabic text. All analysis is done natively in Arabic, leading to greater accuracy.

Your Arabic Sentiment Analysis Company

Repustate's sentiment analysis API is powered by Arabic natural language processing (NLP). It analyzes Arabic data natively, without the need to translate any document into English, thus, giving more accurate and meticulously useful insights.

Table of Contents:

  1. Arabic Sentiment Analysis API
  2. Benefits of Repustate's Arabic Sentiment Analytics
  3. Why Choose Repustate Over Others?
  4. Basic Steps in Arabic Sentiment Analysis
  5. Applications of Sentiment Analysis Tools
  6. Real-World Arabic Sentiment Analysis Examples
  7. Arabic Enterprise Search

Arabic Sentiment Analysis API

Repustate's Arabic sentiment analysis solution is made dedicatedly for the Arabic-speaking world. It understands major Arabic dialects including the Gulf Peninsular, Egyptian, and Levantine Arabic dialects. The tool can be used to analyze data from any Arabic source such as news, social media, blogs, reviews, and surveys.

The solution has its own dedicated Arabic part-of-speech tagger, Arabic lemmatizer, and Arabic-specific sentiment models. It also understands colloquial words and industry jargon. Arabic 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 Arabic sentiment analysis in action

What are the benefits of Repustate's Arabic Sentiment Analytics Tool?

The Repustate Arabic Sentiment Analysis solution is made specifically for Arabic data. It understands 3 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 sentiment analysis by aspect
  • Data security with on-premise deployment or through Cloud
  • Custom-made model specific to your brand, domain, and dialect
  • 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 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 results.
  3. Arabic Text: We never translate. Repustate has unique 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.

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

What are the Basic Steps in Arabic Sentiment Analysis?

Repustate has a massive corpus of Arabic text that has been tagged manually, as the first step towards Arabic 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 :

  1. Collect a massive, highly varied corpus (collection of texts) of the manually tagged Arabic text.
  2. Feed this text into an ML-based algorithm to create an Arabic part-of-speech tagger.
  3. Granulate the algorithm for deeper accuracy using NER.
  4. Extract the sentiment score for each aspect, theme, and topic.

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

Should translations be used for Arabic Sentiment Analysis?

Trying to achieve Arabic sentiment analysis by using an API that uses translations can yield incorrect results. So, the answer is, no. As your Arabic sentiment analysis company, Repustate, uses intricate Arabic 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 (+1 for positive, and -1 for negative) of the data will be inaccurate with translations.

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 news - text, audio & video:

Sentiment analysis from news streams is really easy with Repustate's Sentiment Analysis API. 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.

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.

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.

Let Repustate's Arabic sentiment analysis uncover your hidden insights

Real-World 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 aspect based sentiment analysis of your data. Here are some real-world examples of how Repustate has provided Arabic sentiment analysis to organizations in various industries.

Healthcare Sector:

When the prestigious Nahdi Medical Company, based in Saudi Arabia, approached Repustate, its biggest motivation was the need to understand patients better. They wanted to overhaul the system and deliver a better patient experience. They remained dissatisfied with the speed and accuracy of other tools in the market as they could not grasp the complexity of Arabic. Repustate's sentiment analysis API was at last able to help the client meet its objectives. Our Arabic NLP-powered solution gathered impactful insights more accurately and faster than others. It semantically identified various aspects related to patient care and provided the client with key revelations.

Financial Sector:

A Dubai-based financial corporation realized 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 Arabic sentiment analysis tool provides them with a highly-precise, customized, stock sentiment analysis solution powered by Arabic 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.

Government Sector:

A public transport agency from Egypt wants to improve its service and brand perception and approached Repustate with the problem. They wanted to provide better service by addressing negative feedback and restructuring resources. They wanted to have an authentic and detailed understanding of the sentiment of daily commuters using public modes of transport. Repustate's Arabic sentiment analysis API helped them understand their data. By applying Arabic natural language processing techniques to all the reviews and comments gathered from public forums, Repustate's solution was able to give them useful insights they could use to achieve their goals.

Repustate's Enterprise Search automatically annotates your Arabic data with semantic information. This includes relevant entities, topics, and entity-specific metadata. Search all metadata associated with any given entity that Repustate finds. You can search 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 Arabic Enterprise Search.