Herramienta de análisis del sentimiento del mercado para la toma de decisiones óptimas de trading.
Herramienta de análisis del sentimiento del mercado impulsada por IA, y por data de más de 50,000 fuentes para descubrir las señales tempranas de trading.
Tecnología para el analisis del sentimiento de CryptoMood
Minería de datos a gran escala

Procesamos datos de más de 50.000 fuentes de noticias, más de 10 agregadores de noticias, 4 redes sociales, más de 100 blogs dedicados a trading y criptomonedas

Algoritmos avanzados de Inteligencia Artificial (Análisis del impacto del mercado)

Nuestra herramienta de análisis del sentimiento de criptomonedas utiliza complejos algoritmos de Inteligencia Artificial

Procesamiento natural del lenguaje y aprendizaje automático

Con la ayuda del NLP & ML, las herramientas de análisis de sentimiento de CryptoMood pueden analizar con precisión el texto y medir el sentimiento del mercado de cripto

Movimientos de "ballenas" y emisiones de Tether

Rastreamos los movimientos de grandes carteras y las conversiones significativas de efectivo-cripto-efectivo


Nuestro equipo tiene una amplia experiencia en Inteligencia Artificial, Procesamiento Natural del Lenguaje y Análisis del Sentimiento.

Amir Mamaghani
Fundador y Chief Technology Officer

Amir tiene una maestría en cibernética e IA. Tiene más de 15 años de experiencia en programación y trading algorítmico.

Filip Korbel
Chief Commercial Officer

Emprendedor experimentado y ejecutivo senior en gestión de empresas, ventas, desarrollo de negocios y dirección estratégica

Petr Homola, Ph.D.
Chief Research Officer

Doctor en lingüística computacional, muy activo en la investigación y desarrollo de los algoritmos NLU y NLP más sofisticados. Trabajó para Google y Apple.

Jiří Materna, Ph.D.
Experto en Procesamiento Natural del Lenguaje e IA

Doctor en I.A. y Lingüística Computacional, ex jefe del grupo de investigación de IA en Seznam.cz, coorganizador de la conferencia checa de IA más grande Machine Learning Prague.

Aleš Horák, Ph.D.
Experto en Procesamiento Natural del Lenguaje e IA

Jefe del Departamento de Aprendizaje Automático y Procesamiento de Datos en la Universidad Masaryk en Brno. Doctor y profesor asociado (docente) en informática.

Pavel Rychlý, Ph.D.
Experto en Procesamiento Natural del Lenguaje e IA

Profesor asociado del Departamento de Aprendizaje Automático y Procesamiento de Datos en la Universidad de Masaryk en Brno, y docente en informática

Turing Technology

Turing Technology es un desarrollador fintech con sede en la República Checa. Proporciona análisis de datos, inteligencia artificial y experiencia en machine learning para crear soluciones de software personalizadas para instituciones financieras y brokers. CryptoMood es una rama de Turing.
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Tsar PR es una agencia de comunicaciones de blockchain y fintech con experiencia y pasión por la industria de la cripto. La agencia solo promociona las mejores innovaciones en tecnología financiera y CryptoMood fue seleccionada.
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FPF Capital s.r.o.

FPF apoya proyectos importantes en diversos campos que se relacionan con la tecnología moderna. Eligieron a CryptoMood por ser una de las oportunidades de inversión más prometedoras del mercado.
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Latest News


Preguntas frecuentes

Sentiment analysis is an automated process that decides if a sentence is positive, negative or neutral. It helps to determine the emotion trends that are expressed online.

It is impossible to manually estimate the huge amount of the world’s text data. CryptoMood’s sentiment analysis system does the job through automation

The sentiment index/score is the numerical representation of market sentiment. The score indicates how positive or negative a text is. (The usual system is: -1 for negative, 0 is neutral and +1 is positive.)
Some leading providers of sentiment analysis are:
Hi-Tech BPO
Through a hybrid of approaches that score a sentence or document. The usual algorithmic approaches include:
1. Using vocabulary to look at important keywords (usually verbs and adjectives) along with modifiers like negation words.
2. Using rules. Vocabulary is categorised into chunks using rules to group sentences by parameter.
3. Applying machine learning techniques. A problem is classified and a dataset is amassed. Then features are set up (e.g. keywords).
The system is trained and evolves to identify key data points and improves over time.
To analyse a giant set of data, you need a lot of resources to monitor and rate each data point. This provides the opportunity to better understand historical sentiment trends and to use that analysis to make superior decisions.
VADER is another tool that tells us how positive or negative a text is. It’s a cool name that stands for: Valence Aware Dictionary and sentiment Reasoner. VADER uses Twitter Sentiment Analysis, also known as ‘Opinion Mining’ to analyse conversations, opinions, and viewpoints (all in the form of tweets) to decide business strategy, political analysis, and to assess public actions.
Sentiment data is rated with the help of Natural Language Processing, Artificial Intelligence and machine learning.
We use two different modules: ‘trending’ and ‘live’. ‘Trending’ selects the most important data. ‘Live’ shows all data.
It helps show sentiment when trading crypto by measuring the positivity or negativity of news. If recent news has been bullish and traders are seeing an upward swing, chances are good that the trend will continue.
These are news, portals, media, chat groups, social networks and industry forums. Basically anything in electronic form over the internet that mentions the cryptocurrency markets.
Yes they are named and graphed on our system.
There is no ‘best’. Each has a use in the correct situation.
 lot. E.g. it helps identify a positive or negative mention about a cryptocurrency or company. It is also helps us to detect how a customer reacts to changes.
As part of a university computer science or AI course. Or you can use the CryptoMood platform if you just need real-time crypto market insights.
CryptoMood does that for you so you can concentrate on trading and increase your profit.
– Over 50,000 news and opinion sites 
– 4 major social media networks
– Crypto exchanges 
– Whale wallet tracking 
– Forums and chat groups, and even article commentaries
We have powerful servers that monitor, scrape data and track changes in real-time.
CryptoMood collects and analyses content in English. We are working hard to bring you other major languages from other markets that also impact crypto.
Previous trading experience helps you be a better trader. But you do not need previous trading experience to use CryptoMood.
Previous trading experience helps you be a better trader. But you do not need previous trading experience to use CryptoMood.
Yes, everything is straightforward. Please check the user agreement.
No, this is not possible due to privacy and business concerns.
This solution is available in the CryptoMood business license version.
Your feedback is important to us, so feel free to ask directly over Telegram or Facebook. We currently monitor well over 50,000 sources and this number is growing every day.
Yes, an API is available in the business version.
We are the fastest and most powerful cryptocurrency market analysis tool in the world. CryptoMood is unique, proprietary, and the only solution of its kind currently available to cryptocurrency traders and investors.
We’re a friendly bunch and would love to see you on our Telegram, Facebook or Twitter.
– https://www.facebook.com/CryptoMoodOfficial/
– Telegram @CryptoMoodCom
– Twitter @cryptomood

We use special algorithms that do things like count followers and comments. The AI categorises each source individually and accordingly.

We use all publications, but rate the market impact of each data source and data point individually according to importance, determined by evolving algorithms.

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Ayudamos a mejorar tus decisiones comerciales con el mejor agregador de noticias sobre criptos

Herramienta de análisis del sentimiento del mercado para la toma de decisiones óptimas de trading.
CryptoMood a.s.
IČO: 07922698

Milady Horákové 50, 602 00 Brno, República Checa