计算机科学
大数据
数据科学
过程(计算)
计算模型
比例(比率)
内容分析
动作(物理)
人工智能
数据挖掘
社会科学
量子力学
操作系统
物理
社会学
作者
Seth C. Lewis,Rodrigo Zamith,Alfred Hermida
标识
DOI:10.1080/08838151.2012.761702
摘要
Massive datasets of communication are challenging traditional, human-driven approaches to content analysis. Computational methods present enticing solutions to these problems but in many cases are insufficient on their own. We argue that an approach blending computational and manual methods throughout the content analysis process may yield more fruitful results, and draw on a case study of news sourcing on Twitter to illustrate this hybrid approach in action. Careful combinations of computational and manual techniques can preserve the strengths of traditional content analysis, with its systematic rigor and contextual sensitivity, while also maximizing the large-scale capacity of Big Data and the algorithmic accuracy of computational methods.
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