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.
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
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
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.
Premium Support: As our client, you will have a dedicated engineer assigned to your account.
Technology: We apply artificial intelligence and machine learning to Arabic natural language processing for the best results.
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.
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.
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 :
Collect a massive, highly varied corpus (collection of texts) of the manually tagged Arabic text.
Feed this text into an ML-based algorithm to create an Arabic part-of-speech tagger.
Granulate the algorithm for deeper accuracy using NER.
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
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
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.
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.
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.
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
Arabic Enterprise Search
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.