La API de Análisis de Sentimiento en Redes Sociales devuelve una estructura JSON que contiene el texto analizado, el sentimiento detectado (ya sea "POSITIVO" o "NEGATIVO") y una puntuación de intensidad emocional numérica que varía de -1 a 1.

Los campos clave en los datos de respuesta incluyen "texto" (el texto de entrada), "sentimiento" (la clasificación del sentimiento) y "puntuación" (la intensidad numérica del sentimiento).

Los datos de respuesta están organizados en un formato JSON con tres campos principales: "text" para la entrada original, "sentiment" para la clasificación y "score" para la intensidad emocional, lo que permite un fácil análisis e integración.

El parámetro principal para la API de Análisis de Sentimientos en Redes Sociales es "texto", que debe proporcionarse como entrada. Los usuarios pueden personalizar sus solicitudes variando el contenido del texto que analizan.

Los casos de uso típicos incluyen analizar reseñas de productos, monitorear el sentimiento en redes sociales, mejorar las interacciones del servicio al cliente, realizar encuestas y evaluar el contenido generado por los usuarios en busca de perspectivas emocionales.

La precisión de los datos se mantiene a través de un entrenamiento continuo del modelo y la validación contra conjuntos de datos diversos, asegurando que el análisis de sentimientos refleje el uso del lenguaje en el mundo real y la expresión emocional.

Los usuarios pueden utilizar los datos devueltos integrando el sentimiento y la puntuación en aplicaciones para retroalimentación en tiempo real, análisis de tendencias o respuestas automatizadas en el servicio al cliente y estrategias de marketing.

Los patrones de datos estándar incluyen una clara clasificación de sentimientos y un puntaje correspondiente que indica la intensidad emocional, como "NEGATIVO" con un puntaje de -0.556 para sentimientos negativos.

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