snowdj / computational-communicationLinks
《计算传播学导论》电子书
☆13Updated 10 years ago
Alternatives and similar repositories for computational-communication
Users that are interested in computational-communication are comparing it to the libraries listed below
Sorting:
- A sentiment analysis platform☆48Updated 5 years ago
- 《计算新闻传播学》课程☆109Updated 3 years ago
- NJU Master Course **Big Data Mining and Analysis**☆132Updated 3 years ago
- Code for Chinese LIWC Lexicon Expansion via Hierarchical Classification of Word Embeddings with Sememe Attention (AAAI18)☆157Updated 7 years ago
- 《计算传播学导论》Python代码和PPT☆73Updated 4 years ago
- 南京大学《数据新闻》2017 周一 第3-4节 逸B-210 1-18周☆17Updated 6 years ago
- Weibo-COV: A Large-Scale COVID-19 Social Media Dataset from Weibo☆602Updated last year
- ☆20Updated 4 years ago
- COVID-19-sentiment-analysis-dataset-Weibo☆37Updated 4 years ago
- Machine Learning for Social Scientists☆62Updated 2 years ago
- ASAP: A Chinese Review Dataset Towards Aspect Category Sentiment Analysis and Rating Prediction☆336Updated 4 years ago
- 中文文本分析工具、语料、预训练模型相关资源汇总。☆142Updated 3 months ago
- BTM实现代码☆100Updated 3 years ago
- Dataset of China's-image-related tweets during COVID-19 with aspect-level sentiment labels.☆17Updated 4 years ago
- 🐛 新浪微博社交网络分析&虚假用户检测。衍生应用:生成个性化新浪微博用户报告。☆107Updated 4 years ago
- 自然语言处理导论实验课课件☆43Updated 5 years ago
- Weibo Preprocess Toolkit☆31Updated 6 years ago
- 中文谣言数据☆743Updated 5 years ago
- smp ewect code☆77Updated 4 years ago
- 中文情感分析☆18Updated 9 years ago
- 该仓库收集了常用的中文情感词典,仅供学习☆131Updated last year
- 使用开源的Bert-as-Service预训练生成文档特征向量,基于k-means对COVID-19文献聚类,t-SNE可视化数据,通过LDA为每个簇生成主题关键词,画Bokeh图实现按簇、关键词搜索和筛选数据。☆19Updated 5 years ago
- UCAS研一课程大数据分析的笔记和代码☆35Updated last year
- 用gensim训练LDA模型,进行新闻文本主题分析☆78Updated 6 years ago
- 根据褒贬种子词,利用SO-PMI构建情感词典☆26Updated 9 years ago
- Some very useful python code files.☆18Updated 8 years ago
- SMP 2020年微博情感分类评测任务 第六名解决方案☆69Updated 3 years ago
- Datasets of NCP, contaning news, rumors and legal documents.☆31Updated 4 years ago
- 该资源为调用大连理工情感词典实现的情感分析和情绪分类,并与SnowNLP进行对比。基础性文章,希望对您有所帮助~☆102Updated 4 years ago
- 电商评论观点挖掘☆43Updated 4 years ago