{"id":38225,"date":"2022-10-31T21:18:33","date_gmt":"2022-10-31T13:18:33","guid":{"rendered":"https:\/\/swarma.org\/?p=38225"},"modified":"2022-10-31T21:18:33","modified_gmt":"2022-10-31T13:18:33","slug":"science-advances%ef%bc%9a%e5%a6%82%e4%bd%95%e4%bb%8e%e6%96%87%e6%9c%ac%e6%95%b0%e6%8d%ae%e4%b8%ad%e5%ae%9a%e9%87%8f%e4%bc%b0%e8%ae%a1%e5%9b%a0%e6%9e%9c%e5%85%b3%e7%b3%bb%ef%bc%9f","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=38225","title":{"rendered":"Science Advances\uff1a\u5982\u4f55\u4ece\u6587\u672c\u6570\u636e\u4e2d\u5b9a\u91cf\u4f30\u8ba1\u56e0\u679c\u5173\u7cfb\uff1f"},"content":{"rendered":"
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Dhanya Srudhar, David M. Blei<\/span><\/strong><\/span><\/strong> <\/span>| \u4f5c\u8005<\/strong><\/span><\/strong><\/span><\/strong><\/p>\n

\u90ed\u745e\u4e1c<\/span><\/strong><\/span><\/strong> <\/span>| \u8bd1\u8005<\/strong><\/span><\/strong><\/strong><\/span><\/strong><\/span><\/p>\n

\u9093\u4e00\u96ea<\/span> <\/span>| <\/strong><\/span>\u7f16\u8f91<\/strong><\/p>\n


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How to make causal inferences using texts<\/span><\/p>\n

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\u5728\u6700\u7b80\u5355\u7684\u60c5\u51b5\u4e0b\uff0c\u6587\u672c\u5c31\u662f\u7ed3\u679c<\/span><\/strong>\u3002\u5e72\u9884\u5bfc\u81f4\u6587\u672c\uff0c\u800c\u6587\u672c\u4e0e\u7f16\u7801\u76f8\u5173<\/span>\uff08\u6216\u5bfc\u81f4\u7f16\u7801\uff09<\/span>\u3002\u5728\u8fd9\u91cc\uff0c\u4e0d\u7ba1\u7f16\u7801\u662f\u4ec0\u4e48\uff0c\u5173\u4e8e\u5e72\u9884\u5bf9\u7f16\u7801\u7684\u5f71\u54cd\u7684\u56e0\u679c\u63a8\u65ad\u662f\u6709\u610f\u4e49\u7684\u3002\u5c3d\u7ba1\u5982\u6b64\uff0c\u5e76\u975e\u6240\u6709\u7684\u7f16\u7801\u90fd\u662f\u5e73\u7b49\u7684\u30fc\u30fc\u6709\u4e9b\u7f16\u7801\u53ef\u80fd\u4f1a\u53d7\u5230\u5e72\u9884\u7684\u5f71\u54cd\uff0c\u6709\u4e9b\u5219\u4e0d\u4f1a\u3002\u4e00\u4e2a\u6709\u8da3\u7684\u7814\u7a76\u95ee\u9898\u662f\uff0c\u5982\u4f55\u627e\u5230\u4e00\u4e2a\u7f16\u7801\uff0c\u4f7f\u5176\u5b58\u5728\u53ef\u89c2\u5bdf\u7684\u56e0\u679c\u6548\u5e94\u3002<\/span><\/section>\n
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\u5728 Egami \u7b49\u4eba\u7684\u4f8b\u5b50\u4e2d\uff0c\u6570\u636e\u6765\u81ea\u4e8e\u4e00\u4e2a\u5173\u4e8e\u79fb\u6c11\u7684\u5f00\u653e\u5f0f\u8c03\u67e5\u3002\u5e72\u9884\u6d89\u53ca\u79fb\u6c11\u7684\u72af\u7f6a\u5386\u53f2\u4fe1\u606f\uff0c\u7ed3\u679c\u662f\u53cd\u9988\u8005\u8ba4\u4e3a\u53ef\u80fd\u53d1\u751f\u5728\u79fb\u6c11\u8eab\u4e0a\u7684\u4e8b\u60c5\u7684\u6587\u5b57\u63cf\u8ff0\u3002\u6211\u4eec\u611f\u5174\u8da3\u7684\u662f\u4e0d\u540c\u5e72\u9884<\/span>\uff08\u5386\u53f2\uff09<\/span>\u5982\u4f55\u5f71\u54cd\u8c03\u67e5\u7ed3\u679c\u7684\u67d0\u4e9b\u65b9\u9762\u3002\u4e00\u4e2a\u597d\u7684\u7f16\u7801\u53ef\u4ee5\u6355\u6349\u5230\u8fd9\u4e9b\u65b9\u9762\u3002<\/span><\/section>\n
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\u5728\u5176\u4ed6\u60c5\u51b5\u4e0b\uff0c\u6587\u672c\u662f\u5e72\u9884<\/span><\/strong>\uff0c\u5bfc\u81f4\u7ed3\u679c\u7684\u4e00\u4e2a\u53ef\u80fd\u539f\u56e0\u3002\u5f53\u6587\u672c\u662f\u5e72\u9884\uff0c\u6709\u4e24\u79cd\u6d89\u53ca\u7f16\u7801\u7684\u65b9\u6cd5<\/span>\uff08\u56fe1\uff09<\/span>\u3002<\/span><\/section>\n
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\u56fe1. \u7f16\u7801\u5728\u6d89\u53ca\u6587\u672c\u7684\u56e0\u679c\u6a21\u578b\u4e2d\u53d1\u6325\u4f5c\u7528\u7684\u4e24\u79cd\u65b9\u5f0f\u3002(A) \u7f16\u7801\u6355\u6349\u5bfc\u81f4\u7ed3\u679c\u7684\u6587\u672c; (B) \u7f16\u7801\u8868\u5f81\u5f71\u54cd\u6587\u672c\u5185\u5bb9\u7684\u4e00\u4e9b\u65b9\u9762\u3002| \u6765\u6e90\uff1aAustin Fisher, Science Advances.<\/span><\/p>\n

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\u9996\u5148\uff0c\u7f16\u7801\u53ef\u4ee5\u6355\u6349\u5230\u5bfc\u81f4\u7ed3\u679c\u7684\u6587\u672c\u7684\u4e00\u4e9b\u65b9\u9762<\/span><\/strong>\uff0c\u5982\u56fe1A\u6240\u793a\u3002\u4f8b\u5982\uff0c\u8d37\u6b3e\u7533\u8bf7\u4eba\u5728\u7533\u8bf7\u8d37\u6b3e\u65f6\u4f1a\u5199\u4e00\u4efd\u58f0\u660e\uff0c\u6211\u4eec\u4f1a\u8bb0\u5f55\u4ed6\u4eec\u662f\u5426\u6536\u5230\u8d44\u91d1\u3002\u7f16\u7801\u53ef\u4ee5\u8868\u5f81\u5e94\u7528\u7a0b\u5e8f\u4e2d\u8d37\u6b3e\u4eba\u5458\u6279\u51c6\u6216\u62d2\u7edd\u7533\u8bf7\u65f6\u6240\u4f9d\u8d56\u7684\u6240\u6709\u4fe1\u606f\u3002<\/span>\uff08\u4f7f\u7528\u4e3b\u9898\u6a21\u578b\u7684\u76f8\u5173\u6570\u636e\u7684\u5173\u8054\u5206\u6790\u53ef\u4ee5\u53c2\u8003 [8]\u3002\uff09<\/span>\u5728 Egami \u7b49\u4eba\u7684\u4f8b\u5b50\u4e2d\uff0c\u653f\u6cbb\u5019\u9009\u4eba\u7684\u4f20\u8bb0\u5f71\u54cd\u7740\u4ed6\u4eec\u7684\u53d7\u6b22\u8fce\u7a0b\u5ea6\u3002\u7f16\u7801\u65b9\u7a0b\u80fd\u5c06\u5019\u9009\u4eba\u7684\u4f20\u8bb0\u7b80\u5316\u4e3a\u4e0e\u9009\u6c11\u662f\u5426\u652f\u6301\u5019\u9009\u4eba\u6709\u56e0\u679c\u5173\u7cfb\u7684\u7279\u5f81\u3002<\/span><\/section>\n
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\u5728\u6587\u672c\u4f5c\u4e3a\u5e72\u9884\u7684\u7b2c\u4e8c\u4e2a\u8303\u4f8b\u4e2d\uff0c\u7f16\u7801\u76f4\u63a5\u5f71\u54cd\u6587\u672c\u7684\u5199\u4f5c\u65b9\u5f0f\uff0c\u6587\u672c\u5219\u56e0\u679c\u5730\u5f71\u54cd\u7ed3\u679c<\/span><\/strong>\uff0c\u5982\u56fe1B\u6240\u793a\u3002\u4f8b\u5982\uff0c\u4e00\u4e2a\u5019\u9009\u4eba\u6709\u67d0\u79cd\u653f\u6cbb\u610f\u8bc6\u5f62\u6001\uff0c\u5b83\u4f1a\u5f71\u54cd\u5019\u9009\u4eba\u6f14\u8bb2\u7684\u8bed\u8a00\uff0c\u800c\u6f14\u8bb2\u5f71\u54cd\u5019\u9009\u4eba\u662f\u5426\u5f53\u9009\u3002\u56e0\u679c\u63a8\u7406\u53ef\u4ee5\u5411\u5019\u9009\u4eba\u5efa\u8bae\uff0c\u5982\u4f55\u8c03\u6574\u4ed6\u4eec\u7684\u610f\u8bc6\u5f62\u6001\u7acb\u573a\u4ee5\u5f71\u54cd\u6295\u7968\u884c\u4e3a\u3002<\/span><\/section>\n
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\u5f53\u7f16\u7801\u4ea7\u751f\u6587\u672c\u65f6\uff0c\u4e00\u4e2a\u597d\u7684\u7f16\u7801\u4f1a\u4ece\u5019\u9009\u4eba\u6f14\u8bb2\u7684\u5185\u5bb9\u4e2d\u63a8\u65ad\u51fa\u4ed6\u5fc3\u4e2d\u7684\u610f\u8bc6\u5f62\u6001\u3002\u5728\u8fd9\u4e2a\u610f\u4e49\u4e0a\uff0c\u5728\u4ea7\u751f\u6587\u672c\u4e4b\u524d\uff0c\u7f16\u7801\u662f\u201c\u53ef\u64cd\u4f5c\u7684\u201d<\/span>\uff08\u4f8b\u5982\uff0c\u5019\u9009\u4eba\u53ef\u4ee5\u9009\u62e9\u4ed6\u4eec\u7684\u610f\u8bc6\u5f62\u6001\uff09<\/span>\u3002\u5982\u4f55\u5f62\u6210\u8fd9\u6837\u7684\u7f16\u7801\uff0c\u5373\u4f7f\u662f\u624b\u5de5\u7f16\u7801\uff0c\u4e5f\u662f\u4e00\u4e2a\u56f0\u96be\u7684\u95ee\u9898\uff0c\u56e0\u4e3a\u7406\u60f3\u7684\u7f16\u7801\u4f1a\u6355\u83b7\u6587\u672c\u4f5c\u8005\u7684\u610f\u56fe\u3002<\/span><\/section>\n
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\u5982\u679c\u6211\u4eec\u60f3\u901a\u8fc7\u7b97\u6cd5\uff0c\u4f8b\u5982\u4f7f\u7528\u4e3b\u9898\u6a21\u578b\u6765\u63a8\u65ad\u7f16\u7801\uff0c\u8be5\u600e\u4e48\u505a\uff1f\u975e\u76d1\u7763\u673a\u5668\u5b66\u4e60\u65b9\u6cd5\u867d\u7136\u901a\u5e38\u80fd\u591f\u4ea7\u751f\u53ef\u89e3\u91ca\u7684\u8868\u5f81\uff0c\u4f46\u4e0d\u4e00\u5b9a\u80fd\u591f\u6062\u590d\u8fd9\u6837\u7684\u201c\u53ef\u64cd\u4f5c\u201d\u7f16\u7801\u3002\u5982\u4f55\u6307\u5bfc\u975e\u76d1\u7763\u7684\u65b9\u6cd5\u63d0\u53d6\u8fd9\u6837\u7684\u56e0\u679c\u53d8\u91cf\uff0c\u4e0e\u56e0\u679c\u8868\u5f81\u5b66\u4e60\u8fd9\u4e00\u65b0\u9886\u57df [10] \u76f8\u5173\u3002\u53d1\u5c55\u8bed\u8a00\u6570\u636e\u7684\u56e0\u679c\u8868\u5f81\u5b66\u4e60\u662f\u4e00\u4e2a\u5f88\u6709\u524d\u666f\u7684\u7814\u7a76\u65b9\u5411\u3002<\/span><\/section>\n

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Egami \u7b49\u4eba\u7684\u5de5\u4f5c\u901a\u8fc7\u5c55\u793a\u5982\u4f55\u4ece\u6587\u672c\u6570\u636e<\/span>\uff08\u5176\u4e2d\u6587\u672c\u53ef\u4ee5\u662f\u7ed3\u679c\u6216\u5e72\u9884\uff09<\/span>\u4e2d\u91cf\u5316\u4f30\u8ba1\u56e0\u679c\u5173\u7cfb\uff0c\u63a8\u8fdb\u6587\u672c\u5206\u6790\u548c\u56e0\u679c\u63a8\u65ad\u8fd9\u4e00\u4ea4\u53c9\u5b66\u79d1\u3002\u4ed6\u4eec\u7684\u8bba\u6587\u4ee5\u53ca\u8d8a\u6765\u8d8a\u591a\u5173\u4e8e\u4ece\u6587\u672c\u4e2d\u8fdb\u884c\u56e0\u679c\u63a8\u7406\u7684\u6587\u732e\u4e2d\u53d1\u5c55\u7684\u65b9\u6cd5\uff0c\u53ef\u4ee5\u5e2e\u52a9\u793e\u4f1a\u79d1\u5b66\u5bb6\u548c\u5176\u4ed6\u7814\u7a76\u4eba\u5458\u4ece\u6587\u672c\u6570\u636e\u4e2d\u8fdb\u884c\u65b0\u7c7b\u578b\u7684\u56e0\u679c\u63a8\u7406\u3002<\/span><\/section>\n
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\u53c2\u8003\u6587\u732e<\/span><\/strong><\/span><\/section>\n
1 J. Pearl, Causality (Cambridge Univ. Press, ed. 2, 2009).<\/span><\/section>\n
2 G. Imbens, D. Rubin, Causal Inference in Statistics, Social and Biomedical Sciences: An Introduction (Cambridge Univ. Press, 2015).<\/span><\/section>\n
3 S. Morgan, C. Winship, Counterfactuals and Causal Inference (Cambridge University Press, ed. 2, 2015).<\/span><\/section>\n
4 M. Hernan, J. Robins, Causal Inference: What If? (Chapman & Hall\/CRC, 2020).<\/span><\/section>\n
5 N. Egami, C. Fong, J. Grimmer, M. Roberts, B. Stewart, How to make causal inferences using texts. Sci. Adv. 8, eabg2652 (2022).<\/span><\/section>\n
6 V. Veitch, D. Sridhar, D. Blei, Uncertainty in Artificial Intelligence (Proceedings of Machine Learning Research, 2020).<\/span><\/section>\n
7 M. E. Roberts, B. M. Stewart, D. Tingley, C. Lucas, J. Leder-Luis, S. K. Gadarian, B. Albertson, D. G. Rand, Structural topic models for open-ended survey responses. Am. J. Polit. Sci. 58, 1064\u20131082 (2014).<\/span><\/section>\n
8 O. Netzer, A. Lemaire, M. Herzenstein, When words sweat: Identifying signals for loan default in the text of loan applications. J. Market. Res. 56, 960\u2013980 (2019).<\/span><\/section>\n
9 C. Fong, J. Grimmer, Causal inference with latent treatments. Am. J. Polit. Sci. 10.1111\/ajps.12649 (2022).<\/span><\/section>\n
10 B. Sch\u00f6lkopf, F. Locatello, S. Bauer, N. Ke, N. Kalchbrenner, A. Goyal, Y. Bengio, Towards causal representation learning. arXiv:2102.11107 (2021).<\/span><\/section>\n
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\u672c\u6587\u7ffb\u8bd1\u81ea Science Advances<\/em> \u8bc4\u8bba\u6587\u7ae0\u3002<\/span><\/section>\n
\u539f\u6587\u9898\u76ee\uff1aCausal inference from text: A commentary<\/span><\/section>\n
\u539f\u6587\u94fe\u63a5\uff1ahttps:\/\/www.science.org\/doi\/10.1126\/sciadv.ade6585<\/span><\/section>\n<\/section>\n<\/section>\n<\/blockquote>\n


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\u52a0\u5165\u56e0\u679c\u79d1\u5b66\u793e\u533a<\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n


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\u8be6\u60c5\u8bf7\u89c1\uff1a<\/span><\/p>\n

\u56e0\u679c+X\uff1a\u89e3\u51b3\u591a\u5b66\u79d1\u9886\u57df\u7684\u56e0\u679c\u95ee\u9898 | \u56e0\u679c\u79d1\u5b66\u8bfb\u4e66\u4f1a\u7b2c\u4e09\u5b63\u542f\u52a8<\/a><\/span><\/strong><\/span><\/p>\n

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\u63a8\u8350\u9605\u8bfb<\/span><\/strong><\/strong><\/p>\n