database 文本中情感检测的数据集

Data sets for emotion detection in text

提问by ekka

I'm implementing a system that could detect the human emotion in text. Are there any manually annotated data sets available for supervised learning and testing?

我正在实施一个可以检测文本中人类情感的系统。是否有任何手动注释的数据集可用于监督学习和测试？

Here are some interesting datasets: https://dataturks.com/projects/trending

以下是一些有趣的数据集：https: //dataturks.com/projects/trending

回答by buechel

The field of textual emotion detection is still very new and the literature is fragmented in many different journals of different fields. Its really hard to get a good look on whats out there.

文本情感检测领域还很新，文献分散在不同领域的许多不同期刊中。真的很难好好看看外面的东西。

Note that there a several emotion theories psychology. Hence there a different ways of modeling/representing emotions in computing. Most of the times "emotion" refers to a phenomena such as anger, fear or joy. Other theories state that all emotions can be represented in a multi-dimensional space (so there is an infinite number of them).

请注意，有几种情绪理论心理学。因此，在计算中存在不同的建模/表示情绪的方法。大多数时候，“情绪”是指愤怒、恐惧或喜悦等现象。其他理论指出，所有情绪都可以在多维空间中表示（因此它们的数量是无限的）。

Here are a some (publicly available) data sets I know of (updated):

以下是我所知道的一些（公开可用的）数据集（已更新）：

1. EmoBank. 10k sentences annotated with Valence, Arousal and Dominance values (disclosure: I am one of the authors). https://github.com/JULIELab/EmoBank

2. The "Emotion Intensity in Tweets" data set from the WASSA 2017 shared task. http://saifmohammad.com/WebPages/EmotionIntensity-SharedTask.html

3. The Valence and Arousal Facebook Posts by Preotiuc-Pietro and others: http://wwbp.org/downloads/public_data/dataset-fb-valence-arousal-anon.csv

4. The Affect data by Cecilia Ovesdotter Alm: http://people.rc.rit.edu/~coagla/affectdata/index.html

5. The Emotion in Text data set by CrowdFlower https://www.crowdflower.com/wp-content/uploads/2016/07/text_emotion.csv

6. ISEAR: http://emotion-research.net/toolbox/toolboxdatabase.2006-10-13.2581092615

7. Test Corpus of SemEval 2007 (Task on Affective Text) http://web.eecs.umich.edu/~mihalcea/downloads.html

8. A reannotation of the SemEval Stance data with emotions: http://www.ims.uni-stuttgart.de/data/ssec

1. 电子商务银行。10k 句用价、唤醒和支配值注释的句子（披露：我是作者之一）。https://github.com/JULIELab/EmoBank

2. 来自 WASSA 2017 共享任务的“推文中的情绪强度”数据集。http://saifmohammad.com/WebPages/EmotionIntensity-SharedTask.html

3. Preotiuc-Pietro 和其他人在 Facebook 上发表的价价和唤醒帖子：http://wwbp.org/downloads/public_data/dataset-fb-valence-arousal-anon.csv

4. Cecilia Ovesdotter Alm 的影响数据：http://people.rc.rit.edu/~coagla/affectdata/index.html

5. 由 CrowdFlower https://www.crowdflower.com/wp-content/uploads/2016/07/text_emotion.csv设置的文本数据中的情感

6. ISEAR：http://emotion-research.net/toolbox/toolboxdatabase.2006-10-13.2581092615

7. SemEval 2007 测试语料库（情感文本任务） http://web.eecs.umich.edu/~mihalcea/downloads.html

8. 带有情绪的 SemEval Stance 数据的重新注释：http: //www.ims.uni-stuttgart.de/data/ssec

If you want to go deeper into the topic, here are some surveys I recommend (disclosure: I authored the first one).

如果你想更深入地研究这个话题，这里有一些我推荐的调查（披露：我撰写了第一个）。

1. Buechel, S., & Hahn, U. (2016). Emotion Analysis as a Regression Problem — Dimensional Models and Their Implications on Emotion Representation and Metrical Evaluation. In ECAI 2016.22nd European Conference on Artificial Intelligence (pp. 1114–1122). The Hague, Netherlands (available: http://ebooks.iospress.nl/volumearticle/44864).

2. Canales, L., & Martínez-Barco, P. (n.d.). Emotion Detection from text: A Survey. Processing in the 5th Information Systems Research Working Days (JISIC 2014), 37 (available: http://www.aclweb.org/anthology/W14-6905).

1. Buechel, S., & Hahn, U. (2016)。作为回归问题的情感分析——维度模型及其对情感表示和度量评估的影响。在 ECAI 2016.22nd 欧洲人工智能会议上（第 1114-1122 页）。荷兰海牙（可用：http: //ebooks.iospress.nl/volumearticle/44864）。

2. Canales, L., & Martínez-Barco, P. (nd)。从文本中检测情绪：一项调查。在第 5 个信息系统研究工作日处理（JISIC 2014），37（可获取：http://www.aclweb.org/anthology/W14-6905 ）。