Social Media as an Alternative to Surveys of Opinions About the Economy
Social Media as an Alternative to Surveys of Opinions About the Economy
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DOI：
10.1177/0894439319875692
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发表时间：
2019-09-26
影响因子：
4.1
通讯作者：
Hou, Elizabeth
中科院分区：
文献类型：
--
作者：
Conrad, Frederick G.;Gagnon-Bartsch, Johann A.;Hou, Elizabeth
人们有兴趣使用社交媒体内容来补充甚至替代调查数据。在一项测试这一想法可行性的研究中，奥康纳、巴拉苏布拉马尼扬（Balasubramanyan）、克里奇和史密斯报告说，2008-2009年，包含“工作”一词的推文情绪与基于调查的消费者信心指标之间存在相当高的相关性。其他研究人员报告了2011年的类似关系，但在那之后就不再观察到了，这表明这样的推文可能不像最初希望的那样有希望成为调查回应的替代品。但是，有了正确的分析技术，“工作”推文的情绪可能仍然是一个可以接受的替代方案。为了探索这一点，我们首先将“工作”推文分类为内容与就业相关或不相关的类别，以查看前者的情绪是否与基于调查的消费者情绪指标相关性更高。然后，我们比较了传统的基于词典的方法与为Twitter类文本开发的基于机器学习的新工具确定情感时的关系。我们以三种不同的方式计算了每日情绪，并使用了一种对异常值不敏感的关联性指标。这些方法都没有改善原始数据或最近数据中关系的大小。我们发现，这些分析所需的许多微观决策，如平滑区间的大小和两个系列之间的滞后长度，可以显着影响结果。最后，尽管早期的承诺推文作为调查响应的替代品，我们发现没有证据表明这些数据中的原始关系不仅仅是偶然发生的。
There is interest in using social media content to supplement or even substitute for survey data. In one of the studies to test the feasibility of this idea, O'Connor, Balasubramanyan, Routledge, and Smith report reasonably high correlations between the sentiment of tweets containing the word "jobs" and survey-based measures of consumer confidence in 2008-2009. Other researchers report a similar relationship through 2011, but after that time it is no longer observed, suggesting such tweets may not be as promising an alternative to survey responses as originally hoped. But, it's possible that with the right analytic techniques, the sentiment of "jobs" tweets might still be an acceptable alternative. To explore this, we first classify "jobs" tweets into categories whose content is either related to employment or not, to see whether sentiment of the former correlates more highly with a survey-based measure of consumer sentiment. We then compare the relationship when sentiment is determined with traditional dictionary-based methods versus newer machine learning-based tools developed for Twitter-like texts. We calculated daily sentiment in three different ways and used a measure of association less sensitive to outliers than correlation. None of these approaches improved the size of the relationship in the original or more recent data. We found that the many micro-decisions these analyses require, such as the size of the smoothing interval and the length of the lag between the two series, can significantly affect the outcomes. In the end, despite the earlier promise of tweets as an alternative to survey responses, we find no evidence that the original relationship in these data was more than a chance occurrence.