theoracle/Italian.sentiment.analysis

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license: apache-2.0

tags:
- sentiment
- italian
- news headlines
size_categories:
- "n<1K"

Dataset Description:
General Description: "This dataset consists of Italian news headlines with annotated sentiments. Each headline is enclosed in square brackets followed by the sentiment label 'positive', 'neutral', or 'negative'."
Purpose: "The dataset is designed for training and evaluating sentiment analysis models on Italian-language text, particularly news headlines."

Dataset Structure:
Size and Scope: "The dataset contains a small number of annotated headlines, suitable for initial model training or testing in sentiment analysis tasks."
Data Fields: "Each record includes a 'headline' text field and a 'sentiment' label."
Example:
- headline: "[ mi fa sbagliare tutte le paroleeeee.]"
sentiment: "negative"
- headline: "[ perfetto hai visto poi alla fine anche oggi e passato..]"
sentiment: "neutral"
- headline: "[Rutelli: appoggio al governo #monti, sta lavorando bene #ballarò #osservatoriotivvù]"
sentiment: "positive"

Use Cases:
Sentiment Analysis Model Training: "Researchers and practitioners can use this dataset to develop and train sentiment analysis models for the Italian language."
Academic Research: "The dataset can serve as a basis for studies in computational linguistics focusing on sentiment analysis in Italian news media."

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原始信息汇总

数据集描述

• 概述: 该数据集包含带有情感标注的意大利新闻标题。每个标题用方括号括起来，后跟情感标签“positive”（正面）、“neutral”（中性）或“negative”（负面）。
• 目的: 该数据集旨在用于训练和评估意大利语文本的情感分析模型，特别是新闻标题。

数据集结构

• 规模: 数据集包含少量标注的标题，适合情感分析任务的初始模型训练或测试。
• 数据字段: 每条记录包括一个“headline”（标题）文本字段和一个“sentiment”（情感）标签。
• 示例:
  • 标题: "[ mi fa sbagliare tutte le paroleeeee.]" 情感: "negative"
  • 标题: "[ perfetto hai visto poi alla fine anche oggi e passato..]" 情感: "neutral"
  • 标题: "[Rutelli: appoggio al governo #monti, sta lavorando bene #ballarò #osservatoriotivvù]" 情感: "positive"

使用场景

• 情感分析模型训练: 研究人员和从业者可以使用此数据集来开发和训练意大利语的情感分析模型。
• 学术研究: 该数据集可作为计算语言学领域中，聚焦于意大利新闻媒体情感分析的研究基础。