1. Tweets about political content from elected officials, regardless of party or whether the party is in power, do see algorithmic amplification when compared to political content on the reverse chronological timeline.
2. Group effects did not translate to individual effects. In other words, since party affiliation or ideology is not a factor our systems consider when recommending content, two individuals in the same political party would not necessarily see the same amplification.
3. In six out of seven countries — all but Germany — Tweets posted by accounts from the political right receive more algorithmic amplification than the political left when studied as a group.
4. Right-leaning news outlets, as defined by the independent organizations listed above, see greater algorithmic amplification on Twitter compared to left-leaning news outlets. However, as highlighted in the paper, these third-party ratings make their own, independent classifications and as such the results of analysis may vary depending on which source is used.
二つリンクしてあって片方はブログ記事、片方は論文だけど、自分の感性では後者の方が正式なソースとみなすところ。で、その論文のAbstractには "We present two sets of findings...." とあるわけで、それを著者じゃない人がブログにまとめなおした時勝手に4点を抜き出し直した模様。
半分しか紹介してないじゃん (スコア:2, 興味深い)
公式のサマリーには次の4点が挙げられている。
ストーリーで紹介されているのは3と4だけで1と2は省略されている
これがスラドによる「コンテンツの増幅」か
1. Tweets about political content from elected officials, regardless of party or whether the party is in power, do see algorithmic amplification when compared to political content on the reverse chronological timeline.
2. Group effects did not translate to individual effects. In other words, since party affiliation or ideology is not a factor our systems consider when recommending content, two individuals in the same political party would not necessarily see the same amplification.
3. In six out of seven countries — all but Germany — Tweets posted by accounts from the political right receive more algorithmic amplification than the political left when studied as a group.
4. Right-leaning news outlets, as defined by the independent organizations listed above, see greater algorithmic amplification on Twitter compared to left-leaning news outlets. However, as highlighted in the paper, these third-party ratings make their own, independent classifications and as such the results of analysis may vary depending on which source is used.
Re:半分しか紹介してないじゃん (スコア:1)
×これがスラドによる「コンテンツの増幅」か
○これがスラドによる「コンテンツの削減」か
Re: (スコア:0)
https://gigazine.net/news/20211022-political-content-twitter/ [gigazine.net]
こんな場末の雑談サイトで取り上げんなって事
Re: (スコア:0)
二つリンクしてあって片方はブログ記事、片方は論文だけど、自分の感性では後者の方が正式なソースとみなすところ。で、その論文のAbstractには "We present two sets of findings...." とあるわけで、それを著者じゃない人がブログにまとめなおした時勝手に4点を抜き出し直した模様。