Today's social-media savvy age has considerably changed the paradigm of traditional journalism. Interestingly, it has also led to new debates within the journalism and media industry with supporters of social media terming it as a platform for the masses' voice while opponents terming it as gibberish and noise. Old-school journalism disregards the significance of social media popularity for any article on the pretense of “journalism is not about feeding the masses with whatever crap they want to be fed with.”
It turns out that this entire debate is not as simple as it appears to be on the outlook. What old-school journalism advocates do not take into account is the age-old phenomenon termed as “media bias” by the social sciences research community. A famous paper published in 2004 by the Department of Political Science at UCLA and the Department of Economics at University of Missouri studies the bias of famous news outlets in the US. Since then there have been various attempts at studying biases in traditional media platforms (such as New York Times, Fox News, Washington Post, CBS, Wall Street Journal) with most of these coming from the sciences (social science, political science, Computer Science). Empirical evidence is what is given utmost importance from a scientific viewpoint and unfortunately the social media circles in Pakistan tend to ignore this angle altogether. This brings into the picture a new phenomenon of bias measurement in various forms of media which turns out to be a huge research challenge within itself. The solution: yes, social media with the insights and popularity judgements can serve as a tool not just for the masses' voices but also for measurement of bias in traditional media and this is exactly what a team of researchers in IBA's Web Science group have done.
The crucial nature of the media industry makes it all the more essential to have ways and means of verification of its content. This leads to the natural question of how new media namely the social media can help measure the inevitable biases inherent in traditional media. Few of these questions have been answered by researchers from one of Karachi's most prestigious educational institute, Institute of Business Administration whereby they investigated differences between news appearing on traditional and social media platforms via publicly available data from famous microblog site Twitter. Being a part of this team made me delve deeper into various aspects of media both internationally and in Pakistan with my observation being that today's media tend to ignore the crucial role of social media and does not take into account popular demands. With this conclusion, we argue for a paradigm shift in how traditional media platforms perceive the new media landscape and the sooner they embrace this new world the better for their own survival.
Some technical details of the study warrant an explanation which is as follows. The data mining similarity metric of Jaccard Similarity has been used to investigate the differences in named entity coverage between the 16 million tweets posted during the time period of Egypt uprising (tweets' data obtained from TREC 2011 microblog track) and the New York Times articles corresponding to Egypt. The figure below shows our results:
It demonstrates a significantly low value of coverage (Jaccard Similarity being below 0.5 for all days) thereby proving the presence of media bias. Moreover, we extend this study to a local level (for Pakistani media outlets) on a daily basis for the month of November. The extension utilizes topic models (specifically standard LDA and Twitter-LDA) in order to discover similar topics in the two media followed by a ranking function which computes popularity of a news item in the two platforms. This is then compared with a manually ranked list with the final result being that the ranks obtained from social media (tweets data) match the human-annotated ranks more closely.
For those interested, here's the abstract of our paper:
It is often the case that traditional media provide coverage of a news event on the basis of journalists’ viewpoints - a problem termed in the literature as media bias. On the other hand social media have given birth to an alternative paradigm of journalism known as “citizen journalism”. We take advantage of citizen journalism to detect the bias in traditional media and propose a simple model for empirical measurement of media bias.
Note: This is part of a long-term project by the Web Science research group at Institute of Business Administration, Karachi, Pakistan and we welcome interested students to be a part of our project.
