There is a value in providing a "social news paper for a city" but that's not what OP is doing now. "Swarm" intelligence is superior to an individual. Filtering news articles by number of re-tweets sets higher threshold for signal-to-noise ratio, however, 140 characters hardly constitute a "news article". Below, my suggestion for a data mining web application that is focused on delivering a news paper customized for a city with high signal-to-noise ratio news articles.

Input: X = country, Y = city, tweets from twitter

For each X scan last N million tweets that have a link to a web-site, output M most linked domains (Facebook.com, techcrunch.com, cnn.com, wsj.com, etc) - this gives you a base for news feeds customized for every country

For each Y in X, scan last n thousand tweets that have a link to a web-page, output m most linked web-pages that are hosted on M domains for Y country - this gives you the "social news paper for Y city in X country"

Parameters M and N prevent spamming and shape long term trends. Parameters n and m give you short term trends, which in essence are the "swarm" intelligence about which articles are worth reading for a given city in a given country. The value here is a time saver of what is worth reading to keep up with your community.

Note to self: could be a data mining web app