你可以从该链接(http://thinknook.com/twitter-sentiment-analysis-training-corpus-dataset-2012-09-22/)下载数据集。 加载数据并提取所需变量(情感及情感文本)。 该数据集包含 1,578,614 个分好类的推文,每一行都用 1(积极情绪)和 0(消极情绪)进行了标记。 作者建议用 1/10 的数据进行测试,其余数据用于训...
stratify=data['sentiment']) print(x_train.shape, x_test.shape, y_train.shape, y_test.shape) (1417523,) (157503,) (1417523,) (157503,) 将测试集标签存储在硬盘上以便后续使用。 pd.DataFrame(y_test).to_csv('./predictions/y_true.csv', index=False, encoding='utf-8') 接下来就可以应用...
'SentimentText'])data.columns= ['sentiment', 'text']datadata= data.sample(frac=1,random_state=42)print(data.shape)(1578614, 2)for row in data.head(10).iterrows():print(row[1]['sentiment'], row[1]['text'])1 http://www.popsugar.com/2999655 keep voting for robert pattinson in the...
中文情感分析,CNN,BI-LSTM,文本分类. Contribute to linguishi/chinese_sentiment development by creating an account on GitHub.
theinvestorsentimentindexofthedaywascalculatedaccordingtotheresultsofthe sentimentclassification,andthesamesentimentindexwascalculatedforthenews data.Then,theobtainedinvestorsentimentindicatorsandnewssentimentindicators 1 ResearchonCNN-LSTM-AMStockFluctuationPredictionModelIntegratingNewsandInvestorSentiment ...
本文是我之前写过的一篇基于推特数据进行情感分析的文章(https://ahmedbesbes.com/sentiment-analysis-on-twitter-using-word2vec-and-keras.html)的延伸内容。那时我建立了一个简单的模型:基于 keras 训练的两层前馈神经网络。用组成推文的词嵌入的加权平均值作为文档向量来表示输入推文。
This study is to develop a sentiment analysis system for customers' review on a scenic site. It is based on Convolutional Neural Networks (CNNs) built on Long Short-Term Memory (LSTM) models for text feature extraction under a deep learning framework. The CNNs built on LSTM models applies ...
The CNN models discussed herein improve upon the state of the art on 4 out of 7 tasks, which include sentiment analysis and question classification. 我简单翻译下,英文不好见谅 我们发表了基于卷积神经网络(CNN)在预先训练的单词向量上进行训练的多项实验,用于句级别的文本分类任务。实验中我们发现,通过...
increasing investor sentiment in the network structure.The empirical part makes a comparative experimental analysis based on Shanghai stock index in China.By comparing the experimental prediction results and evaluation indicators,it verifies the prediction effectiveness and feasibility of ISI-CNN-LSTM ...
Sarcasm is a term that refers to the use of words to mock, irritate, or amuse someone. It is commonly used on social media. The metaphorical and creative nature of sarcasm presents a significant difficulty for sentiment analysis systems based on affective computing. The technique and results of...