When I was envisaging this research, I only saw it from a citizen journalist’s perspective. The picture goes something like in Figure:
But reading Basu, I have seen there are more elements to how ‘voices’ get amplified. The amplification and trust in the news is filtered through algorithms.
“Google, Facebook, Twitter and YouTube are among the new intermediaries through which millions of us access news. Media scholar Justin Schlosberg (2016) refers to them as ‘gateways’. Manuel Castells (2009), though critical of global media corporations, argues that social networking sites offer the means of ‘mass self communication’. They enable users to produce meaning interactively. Anyone can tweet, post or upload a video.”
The literature, however, shows that “gateways actually tend to lead users back to mainstream news brands. For example, Schlosberg (2016: 120–2) reveals that Google’s news algorithm systematically favours large-scale and incumbent providers. Its ranking of stories is not only matched to the keywords of a search: it gives prior weighting to news providers based on a range of what it considers indicators of news quality. These include the size of audience, the size of newsroom, and the volume of outpout. When it comes to volume, it favours providers that offer a breadth of coverage over specialist media, and those that produce a lot of coverage on topics that are also receiving a lot of attention on the web as a whole. Thus, the algorithm favours established providers that pursue a dominant news agenda.”
“There’s a feedback loop at work here. Because these outlets are dominant, Google prioritises them, which, in turn, reinforces their dominance. As Schlosberg points out, given its stated preference for sources like CNN and the BBC, it may also be reinforcing a news agenda with a ‘western’ bias (122).
So how does a feedback loop get modelled and measured?
I keep leaning back to my data analysis as a a solution but I’m not sure that’s right. What if the data collection method was more aligned with journalism? How do journalists get data?
Vox pops? radio station call-ins? letter pages? The last two would hardly be a guarantee of an unbiased representative sample but a vox pop might be useful if it was done long enough and with a broad enough selection of locations.
It could be simple — have you heard of the mayor’s faith advisor, diesel fleet of vehicles, Bristol Housing Festival?
Do you rent, own, etc.?
Could their demographics be assumed by the questioner? how much bias might that introduce to the data analysis?
And time would need to be added as well! I’ve written about the dispersal rate of information — a decay effect in essence.