Suchergebnisse

Stephen Colbert hosts a comedy television program called The Colbert
Report (the t at the end is silent—both of them!) in which he
parodies personality-based news shows like The O'Reilly Factor that have
become popular during the last 10 years. In an effort to make fun of these (usually
conservative) personalities who engage in non-stop self-promotion, Colbert frequently trades
outlandish claims for laughs. Among these is the claim that anyone who comes on the
Report receives the "Colbert bump," immediately vaulting the guest to
stardom, fame, and fortune. Like Midas turning everything he touches to gold, Stephen
Colbert can turn losers into winners, just by interviewing them on his show (but, ahem, he
would never actually interview a loser now would he?).

Using large-scale network analysis I map the cosponsorship networks of all 280,000 pieces of legislation proposed in the U.S. House and Senate from 1973 to 2004. In these networks, a directional link can be drawn from each cosponsor of a piece of legislation to its sponsor. I use a number of statistics to describe these networks such as the quantity of legislation sponsored and cosponsored by each legislator, the number of legislators cosponsoring each piece of legislation, the total number of legislators who have cosponsored bills written by a given legislator, and network measures of closeness, betweenness, and eigenvector centrality. I then introduce a new measure I call "connectedness" which uses information about the frequency of cosponsorship and the number of cosponsors on each bill to make inferences about the social distance between legislators. Connectedness predicts which members will pass more amendments on the floor, a measure that is commonly used as a proxy for legislative influence. It also predicts roll call vote choice even after controlling for ideology and partisanship.