Repustate's sentiment analysis API is powered by French natural language processing (NLP). It analyzes French data natively, without the need to translate any document into English, thus, giving more accurate and meticulously useful insights.
Repustate's French sentiment analysis solution is made dedicatedly for the French-speaking world. The tool can be used to analyze data from any French source such as news, social media, blogs, reviews, and surveys.
The solution has its own dedicated French part-of-speech tagger, French lemmatizer, and French-specific sentiment models. It also understands colloquial words and industry jargon. French 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 French sentiment analysis in action
What are the benefits of Repustate's French Sentiment Analytics Tool?
The Repustate French Sentiment Analysis solution is made specifically for French 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:
Obtain granular French 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.
Premium Support: As our client, you will have a dedicated engineer assigned to your account.
Technology: We apply artificial intelligence and machine learning to French natural language processing for the best results.
French Text: We never translate. Repustate has unique speech taggers and sentiment models made just for French 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.
French Language Sentiment Models
Repustate has developed sentiment language models specific to French
to capture the various phrases, idioms, and expressions that help define certain sentiments. It turns unstructured
French data into business intelligence you can use to increase your value proposition, brand experience, and value delivery.
Take a quick tour of Repustate's French text analytics solution
What are the Basic Steps in French Sentiment Analysis?
Repustate has a massive corpus of French text that has been tagged manually,
as the first step towards French 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 French text.
Feed this text into an ML-based algorithm to create an French part-of-speech tagger.
Granulate the algorithm for deeper accuracy using NER.
Extract the sentiment score for each aspect, theme, and topic.
Repustate uses French Named Entity Recognition (NER) with
advanced semantic search to identify brand and business entities in data. No matter how misspelled a word is,
the French 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 French sentiment analysis?
Trying to achieve French sentiment analysis by using an API that uses translations can
yield incorrect results. So, the answer is, no. As your French sentiment analysis company,
Repustate, uses intricate French 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 French NLP in Sentiment Analysis Tools
Repustate's French 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 French 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 French 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 French sentiment analysis uncover your hidden insights
Real-World Applications of French Text Sentiment Analysis
Repustates's French sentiment analysis API is made for the French language and its dialects.
Powered by French 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 French
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 French. Repustate's sentiment analysis API was at last
able to help the client meet its objectives. Our French 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 Paris-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 French sentiment analysis tool provides them with a highly-precise,
customized, stock sentiment analysis solution powered by French 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 Marseille 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 French sentiment analysis API helps them understand their data. By applying
French 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.
French Enterprise Search
Repustate's Enterprise Search automatically annotates
your French 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 French Enterprise Search.
Toutes les langues ne sont pas les mêmes
Les règles de grammaire varient d'une langue à l'autre. Les règles de conjugaison des verbes, l'accord nom-verbe et les négations varient d'une langue à l'autre.
Le français est une langue unique et elle diffère de l'anglais de plusieurs façons. Utiliser les mêmes techniques et les mêmes modèles de langue qui fonctionnent pour l'analyse des sentiments de l'anglais lors qu'on effectue l'analyse des sentiments de français donnerait des résultats horriblement imprécis.
Voilà pourquoi Repustate a conçu des outils propress à français pour aider à l'analyse des sentiments de français, y compris un étiqueteur morpho-syntaxique de français, un lemmatiseur de français et, bien sûr, des modèles de sentiments propres à français.
Étiquetage morpho-syntaxique de français
L'étiquetage morpho-syntaxique de français permet à Repustate de cerner l'endroit où les sentiments peuvent se situer dans un bloc de texte. Verbes, noms et adjectifs fournissent les indices nécessaires pour déterminer les sentiments.
Afin de créer un étiquetage morpho-syntaxique rapide et précis de français, vous devez avoir un corpus massif de texte de français manuellement étiqueté. Ce texte de français peut ensuite être introduit dans un algorithme d'apprentissage automatique pour créer un étiqueteur morpho-syntaxique de français.
Plus le corpus est grand, et plus important encore, plus le corpus est varié, plus les résultats dans la création de l'étiqueteur morpho-syntaxique de français. Repustate a créé un corpus massif de texte de français saisissant des données de diverses sources pour assurer une bonne couverture.
Les modèles de sentiments de langue de français
Repustate a conçu des modèles de sentiments de langue propres à français pour saisir les diverses syntagmes, locutions et expressions qui aident à définir les sentiments en écrivant en français. Comprendre les différents aspects grammaticaux de la langue français qui la rendent unique et très différente de l'anglais est ce qui permet à l'analyse des sentiments de français de Repustate d'être aussi rapide et précise qu'elle est.