Unlock the meaning in your Hebrew data

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

Your Hebrew Sentiment Analysis Company

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

Table of Contents:

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

Hebrew Sentiment Analysis API

Repustate's Hebrew sentiment analysis solution is made dedicatedly for the Hebrew-speaking world. The tool can be used to analyze data from any Hebrew source such as news, social media, blogs, reviews, and surveys.

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

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

The Repustate Hebrew Sentiment Analysis solution is made specifically for Hebrew 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:

  • Understand your Hebrew speaking customers
  • Visualize all the insights in a customer insights dashboard
  • Obtain granular Hebrew 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.

  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 Hebrew natural language processing for the best results.
  3. Hebrew Text: We never translate. Repustate has unique speech taggers and sentiment models made just for Hebrew 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.

Hebrew Language Sentiment Models

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

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

What are the Basic Steps in Hebrew Sentiment Analysis?

Repustate has a massive corpus of Hebrew text that has been tagged manually, as the first step towards Hebrew 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 Hebrew text.
  2. Feed this text into an ML-based algorithm to create an Hebrew 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 Hebrew Named Entity Recognition (NER) with advanced semantic search to identify brand and business entities in data. No matter how misspelled a word is, the Hebrew 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 Hebrew sentiment analysis?

Trying to achieve Hebrew sentiment analysis by using an API that uses translations can yield incorrect results. So, the answer is, no. As your Hebrew sentiment analysis company, Repustate, uses intricate Hebrew 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 Hebrew NLP in Sentiment Analysis Tools

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

Repustate's Hebrew 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 Hebrew 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 Hebrew 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 Hebrew sentiment analysis uncover your hidden insights

Real-World Applications of Hebrew Text Sentiment Analysis

Repustates's Hebrew sentiment analysis API is made for the Hebrew language and its dialects. Powered by Hebrew 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 Hebrew sentiment analysis to organizations in various industries.

Healthcare Sector:

A Haifa-based healthcare corporation wants to understand the doctor-patient relationship to make the whole system more sensitive towards healthcare, Repustate's Hebrew 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 Haifa-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.

Financial Sector:

A Tel Aviv-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 Hebrew sentiment analysis tool provides them with a highly-precise, customized, stock sentiment analysis solution powered by Hebrew 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 Acre 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 Hebrew sentiment analysis API helps them understand their data. By applying Hebrew 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.

Repustate's Enterprise Search automatically annotates your Hebrew 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 Hebrew Enterprise Search.

לא כל השפות אותו דבר

חוקי הדקדוק שונים משפה לשפה. החוקים של הטיית פעלים, התאמת שם-פועל ושלילה, שונים משפה לשפה.

עברית היא שפה ייחודית והיא שונה מאנגלית מכמה בחינות. אם נשתמש בשיטות ובמודלים הלשוניים שעובדים בניתוח רגשי באנגלית כשנבצע ניתוח רגשי בעברית, נקבל תוצאות מאוד-מאוד לא מדויקות.

מסיבה זו פותחו ב-Repustate כלים מוגדרי-עברית לסיוע בניתוח רגשי בעברית, ובהם מתייג חלקי דיבר בעברית, מזהה צורת בסיס (lemmatizer) בעברית, וכמובן, מודלים רגשיים מוגדרי-עברית .

תיוג חלקי הדיבר בעברית

תיוג חלקי הדיבר בעברית מאפשר ל-Repustate להתביית על על המקום המדויקו שבו טמון הרגש בתוך גוש טקסט. פעלים, שמות עצם ושמות תואר, מספקים את הרמזים הדרושים כדי לזהות רגש.

כדי ליצור מתייג חלקי דיבר בעברית שיהיה מהיר ומדויק, דרוש קורפוס גדול של טקסטים בעברית שתויגו ידנית. הטקסטים בעברית יוזנו לאלגוריתם למידה חישובית כדי ליצור מתייג חלקי דיבר בעברית.

ככל שהקורפוס יהיה גדול יותר, וחשוב מכך - ככל שיהיה מגוון יותר, התוצאות של יצירת מתייג חלקי שפה בעברית יהיו טובות יותר. Repustate הקימו קורפוס גדול של טקסטים בעברית, ובו נתונים שנאספו ממקורות שונים, כדי להבטיח כיסוי נרחב.

מודלים רגשיים בעברית

Repustate פיתחו מודלים לשוניים רגשיים ספציפיים לעברית , במטרה ללכוד את מגוון הצירופים, שימושי הלשון והביטויים שעוזרים להגדיר רגש בכתיבה בעברית. הבנת ההיבטים הדקדוקיים השונים של העברית, שמייחדים אותה ועושים אותה שונה מאוד מאנגלית, היא שמאפשרת ניתוח רגשי מהיר ומדויק בעברית כמו זה שפותח ב- Repustate.