The video we had been assigned was about partisanship and search for engaging news by Dr Natalie Stroud. We were exposed to the filter bubble effect in the previous readings and this video gave another perspective into selective exposure, moral foundation and stereotype exposure model. News organization these days are trying to engage with the audience and yes, they do succeed in effecting the thought process of the audience. At least in India, political election results are often determined by the party the dominant news channel of the region supports. This support has led to stable parties being toppled by new emerging political parties. I am focusing on the influence of media and other outlets on audience.
My major concern is as a newbie or a new joiner to any community one must have all the information and then decide if he wants to believe or oppose the particular ideology. This would make sure that unknowingly the person does not start following and believing the ideology. There is something known as a Media Bias chart [1] which depicts all major media outlets on a chart based on their liberal and conservative stance. Similar to that, a “bias index” could be created which would determine from past history the tendency of the particular media outlet to be bias and not only in terms of political belief. It is a way to ensure that people are informed about the stance of the news outlet. Other affiliations should also be made transparent. Social media platforms like YouTube, Twitter, Facebook have incorporated a sort of #Ad feature. This helps the user of the platform to form an informed judgement.
Journalism should be unbiased, however as the speaker had pointed out the factor of “What sells?” plays an important role. This determines what articles are promoted, the breaking news etc. It is true that human nature demands controversy. Negative publicity is what is popular and is received well by a certain sector. So, to analyze how an information is perceived by the audience a live voting mechanism can be incorporated to measure people perception, something similar to the feedback model of Facebook live for news outlets. A simple upvote and downvote system, where the user can text in their “Yes” or “No” opinion and according to the result the number of votes change. This would help formulate the user rating into an index. Let’s call this the “perception index”. It would give a comprehensive idea of what the audience feels about the media outlet. This will be applicable to live television broadcast or digital media and not the print media. Both the perception and the bias index would be a great judgement of the partisanship of the news outlet.
The bias index would be an index reflecting from prior data (considering certain parameters for determining bias). The bias parameters should be known and available to the audience to avoid prejudice in determining the index and to promote awareness. The perception index on the other hand is an indicator of what is perceived at the moment (rather than the past). This would make things transparent as it would not have any predefined parameters. Considering both the indexes a total index can be calculated. I believe that this sort of a model would encourage people to get out of the filter bubble and be more aware.
[1] https://www.adfontesmedia.com/media-bias-chart-3-1-minor-updates-based-constructive-feedback/
