通过大规模微博数据量化中国人的幸福感

Chong Kuang, Zhiyuan Liu, Maosong Sun, Feng Yu, Pengfei Ma
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引用次数: 3

摘要

幸福是衡量我们生活满意度的一个重要指标。微博数据可以反映用户的生活水平和心理状态。我们基于PERMA词典和新浪微博的大规模微博数据,采用PMI和分布相似相结合的方法构建了一个大型词典。在此基础上,提出了一种基于PERMA理论的幸福感定量计算方法。实验表明,与基线相比,我们的方法在AP和Bpref方面分别取得了显著的改进。在对人工标注数据集进行验证后,我们使用我们的方法对大规模微博数据进行了深入分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantifying Chinese Happiness via Large-Scale Microblogging Data
Happiness is an important indicator to measure our life satisfaction. Microblogging data can reflect users' living standards and psychological state. We build a large lexicon based on the PERMA lexicon and large-scale microblogging data on Sina Weibo by combining the PMI and distrabutional similarty method. Using this lexicon, we propose a method to calculate the happiness quantitatively based on PERMA theory. Experiments shows that our method achieve significant improvement compared with the baseline in terms of AP and Bpref respectively. After the verification of our method on manual annotation dataset, we perform an in-depth analysis on large-scale microblogging data using our method.
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