text: The automatic content analysis of mass media in the social sciences has become necessary and possible with the raise of social media and computational power. One particularly promising avenue of research concerns the use of opinion mining. We design and implement the POPmine system which is able to collect texts from web-based conventional media (news items in mainstream media sites) and social media (blogs and Twitter) and to process those texts, recognizing topics and political actors, analyzing relevant linguistic units, and generating indicators of both frequency of mention and polarity (positivity negativity) of mentions to political actors across sources, types of sources, and across time.
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  @cite_3: Content analysis is one of the most important but complex research methodologies in the social sciences. In The Content Analysis Guidebook author Kimberly Neuendorf provides an accessible core text for upper-level undergraduates and graduate students across the social sciences. Comprising step-by-step instructions and practical advice, this text unravels the complicated aspects of content analysis. The Content Analysis Guidebook provides readers: • Numerous examples from across the social sciences • Sidebars that describe innovative and wide-ranging content analysis projects, from both academia and commercial research • Pedagogical tools in an easy to understand format
  @cite_6: Abstract While scholars have studied the manner in which the Christian Right supported President Reagan, they have neglected to examine Reagan's support for the Christian Right. The purpose of this research to is analyze the public support Reagan accorded the legislative objectives of the Christian Right, through an examination of his State of the Union addresses. Among the findings are that Reagan devoted limited (but significant) attention to the social issues, focused primarily on the need for traditional values, anti-abortion, and school prayer legislation, and employed rather restrained language in support of the social issues.
  @cite_15: In choosing and displaying news, editors, newsroom staff, and broadcasters play an important part in shaping political reality. Readers learn not only about a given issue, but also how much importance to attach to that issue from the amount of information in a news story and its position. In reflecting what candidates are saying during a campaign, the mass media may well determine the important issues—that is, the media may jet the "agenda" of the campaign. The authors are associate professors of journalism at the University of North Carolina, Chapel Hill.
  @cite_13: Examination of the increasing number of articles employing quantitative content analysis in 1971–95 Journalism & Mass Communication Quarterly showed primary focus on news editorial content in U.S. media. Nearly half examined newspapers, and half were coauthored. Most used convenience or purposive samples. Few involved a second research method or extra-media data, explicit theoretical grounding, or research questions or hypotheses. Half reported intercoder reliability, and two-fifths used only descriptive statistics. Analysis of trends shows growth in coauthorship and reporting of reliability, and increasing emphasis on more sophisticated statistical analysis. No parallel trend exists, however, in use of explicit hypotheses research questions or theoretical grounding.
  @cite_11: The increasing availability of digitized text presents enormous opportunities for social scientists. Yet hand coding many blogs, speeches, government records, newspapers, or other sources of unstructured text is infeasible. Although computer scientists have methods for automated content analysis, most are optimized to classify individual documents, whereas social scientists instead want generalizations about the population of documents, such as the proportion in a given category. Unfortunately, even a method with a high percent of individual documents correctly classified can be hugely biased when estimating category proportions. By directly optimizing for this social science goal, we develop a method that gives approximately unbiased estimates of category proportions even when the optimal classifier performs poorly. We illustrate with diverse data sets, including the daily expressed opinions of thousands of people about the U.S. presidency. We also make available software that implements our methods and large corpora of text for further analysis.
summary: Content analysis of mass media has an established tradition in the social sciences, particularly in the study of effects of media messages, encompassing topics as diverse as those addressed in seminal studies of newspaper editorials @cite_7 , media agenda-setting @cite_15 , or the uses of political rhetoric @cite_6 , among many others. By 1997, Riffe and Freitag @cite_13 , reported an increase in the use of content analysis in communication research and suggested that digital text and computerized means for its extraction and analysis would reinforce such trend. Their expectation has been fulfilled: the use of automated content analysis has by now surpassed the use of hand coding @cite_3 . The increase in the digital sources of text, on the one hand, and current advances in computation power and design, on the other, are making this development both necessary and possible, while also raising awareness about the inferential pitfalls involved @cite_11 @cite_8 .