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chinesenlpcorpus's Issues

豆瓣评论限制问题

豆瓣的影评现在只能最多查看500页的信息,请问是怎么做到爬取数万条影评信息的呢?

waimai_10k.csv的编码问题

您好,我使用pd.read_csv()读取waimai_10k.csv数据,却发现始终存在编码问题,尝试了各种编码均不行;请问您使用了什么预处理手段达到您intro.ipynb那样没有编码错误的展示吗

论文中可否引用该数据?

本科毕业论文想引用豆瓣影评中的一些数据。想请问本数据可否引用,若引用参考文献中怎么写才好?谢谢(#^.^#)

Weibo senti 100k is very likely labelled by the emoticons

I downloaded this dataset(ChineseNlpCorpus/datasets/weibo_senti_100k) to train a model for chinese sentiment analysis. Upon treating this dataset I observed that 100% of the posts contain emoticons. Here is the distribution of the top10 emoticons according to the positive and negative polarity:

1013 emoticons in total. They are: [('泪', 44489), ('哈哈', 40510), ('嘻嘻', 22370), ('抓狂', 17262), ('鼓掌', 15923), ('爱你', 12685), ('怒', 12011), ('衰', 10466), ('晕', 9440), ('偷笑', 8375)]

710 emoticons in the positive set. They are: [('哈哈', 35764), ('嘻嘻', 20115), ('鼓掌', 14836), ('爱你', 11349), ('偷笑', 5223), ('太开心', 3820), ('可爱', 3809), ('心', 2122), ('赞', 1991), ('给力', 1976)]

695 emoticons in the negative set. They are: [('泪', 43248), ('抓狂', 16643), ('怒', 11830), ('衰', 10202), ('晕', 9022), ('哈哈', 4746), ('偷笑', 3152), ('蜡烛', 2887), ('汗', 2456), ('嘻嘻', 2255)]

I trained a very simple model to classify and I obtained 98% of accuracy in 2 epochs. Therefore, the emoticons have a strong bias in the classification. It led me to conclude that this dataset is not manually annotated. Probably whoever annotated the dataset manually classified some frequent emoticons and use them to tag the posts. Just saying for anyone who want to gather this data, you'd probably like to clean the emoticons out of it to avoid bias.

Peace!

yf_amazon数据集来源问题

您好,看到您在对yf_amazon数据集进行介绍时,描述的是“数据来源:亚马逊”,但是在原数据集地方写的是“JD.com E-Commerce Data,Yongfeng Zhang 教授为 WWW 2015 会议论文而搜集的数据”,在具体的数据集评论中发现确实存在“亚马逊”等字眼,所以想跟您确认一下yf_amazon数据集的来源,谢谢!

数据集reply不全

为什么金融数据集里面的reply一项很多后面都带有省略号,这不是不全吗

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