【時事英文】當心!臉書演算法將你困在「同溫層」中

   

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封面圖|Flicker__ Eduardo Woo CC by 2.0

美國大選後,臉書動態分成了兩個平行社會:一為人們大肆慶祝川普當選,二為人們對川普勝選感到驚訝。當臉書迎合我們喜好遞送內容,我們只看見與自己觀點相同的文章,不感興趣的貼文逐漸減少,最終形成一個個同溫層。現在,希望能跟大家一起,透過新聞練習英文閱讀,同時了解國際時事。

Facebook's algorithm knows what you like based on the videos you watch, people you talk to, and content you interact with. It then shows you more of the same. This creates something called "filter bubbles." You begin to see only the content you like and agree with, while Facebook (FB, Tech30) hides dissenting points of view.

臉書演算法決定你看見的世界。臉書演算法根據你喜歡的影片、交談對象及感興趣的貼文,提供客製化的內容,形成所謂的過濾氣泡(filter bubbles),亦可稱為同溫層。你只看到自己喜愛及認同的內容,不感興趣的貼文逐漸減少。

This means news on Facebook comes with confirmation bias -- it reinforces what you already think is true -- and people are increasingly frustrated.

臉書讓人陷入單一認同,強化個人感受,卻無助於辨別真相及傾聽多元聲音。

Facebook denies it's a media company, yet almost half of U.S. adults get news from Facebook.

近半數的美國人靠臉書獲取新聞,臉書卻否認自己是媒體。(註:臉書執行長祖克柏多次表示,臉書是科技公司,提供分享及接收資訊的平台,而不是負責生產內容的媒體。)

When Facebook fired its human curators and began to rely on algorithms to surface popular stories earlier this year, fake news proliferated.

今年稍早,臉書大幅裁員人工編輯,交由演算法過濾文章,導致假新聞氾濫。

Viral memes and propaganda spread among people with similar beliefs and interests. It's cheaper and easier to create and spread ideological disinformation than deeply-researched and reported news. And it comes from all over -- teens in Macedonia are responsible for a large portion of fake pro-Trump news, according to a BuzzFeed analysis.

不實新聞在同溫層中病毒式擴散。以假亂真的文章,比長篇深度報導更吸引眼球。根據BuzzFeed報導,有群年輕人在馬其頓創立假新聞網站,他們靠產出川普的不實報導,獲取高額利潤。

Filter bubbles became especially problematic during the presidential election.

過濾氣泡問題在美國大選期間越演越烈。

Hyperpartisan news sites and fake websites distributed false stories about voter fraud, election conspiracies, and the candidates' pasts that spread like wildfire on Facebook. It was more prevalent on right-leaning Facebook pages. As CNNMoney's Brian Stelter said in response to the growing number of false viral stories, people should have a "triple check before you share" rule.

政治或單一黨派觀點的新聞及不實消息在社群媒體亂竄。有線電視新聞網(CNN)媒體評論員史特爾特(Brian Stelter)表示,面對假新聞氾濫問題,人們須注意一個原則:「分享文章前,再三確認。」

Today, many people are shocked by Trump's victory. Words of fear and sorrow fill their Facebook feeds, and even those with thousands of friends are probably only seeing posts that echo their feelings.

許多人對川普勝選感到訝異,他們的臉書充滿恐懼及悲傷的貼文。對擁有數千位朋友的人來說,他只能看到與其觀點相同的少部分文章。

But if you voted for Trump, chances are your feed reflects the opposite. You might see a cascade of #MakeAmericaGreatAgain hashtags and friends celebrating.

但你若是川普的支持者,動態牆會截然不同,你會看到朋友們大肆慶祝及#MakeAmericaGreatAgain (#讓美國再次偉大)。

Facebook will likely face questions about its responsibility to weed out fake sites and false stories. The company did not respond to questions about whether it plans to modify the news feed algorithms. On an earnings call in July, Facebook CEO Mark Zuckerberg argued that social media sites actually provide more diversity of opinion than traditional news outlets.

七月臉書執行長祖克柏(Mark Zuckerberg)表示,相較於傳統媒體,社群媒體提供更多元的觀點。近來,各界呼籲臉書負起過濾不實內容的責任。然而,臉書公司尚未回應此事。(註:祖克柏於13日發表聲明,強調假新聞不可能改變大選結果。)

圖取自CNN網站

圖取自CNN網站

  • But Facebook is just the vehicle with which friends and family are sharing news. It's not necessarily about trusting the news people see on Facebook, but believing and trusting the people who are sharing it.

臉書提供人們工具,分享新聞及貼文。比起確認新聞的真實性,人們更相信分享文章的朋友。

The U.S. presidential election starkly illustrated the problems with filter bubbles and personalized social networks. Almost two billion people use the social media site where friends and family share and nurture similar beliefs and false news snowballs. And it raises questions as to the civic responsibility of the world's biggest platform -- and whether or not automated fact-checking could have changed an election.

美國大選凸顯了過濾氣泡問題。近二十億人使用社群媒體,人們只與自己觀點相似的人溝通,假新聞藉同溫層病毒式傳播。再者,臉書作為最大的資訊分享及接收平台,是否把關假新聞間接影響大選結果。

 

編註:同溫層助長假新聞,而假新聞間接助選川普。近期,假新聞問題鬧得沸沸揚揚,臉書教主祖克柏如何回應呢?

2. 「有圖就有真相?」教你9招辨別新聞真偽

編註:當不實消息鋪天蓋地而來,聳動標題、內容不實的文章充斥社群媒體,我們該如何分辨新聞真假呢?

參考資料》

1. 臉書究竟會讓公民社會更有活力或是反而走向極端?

2. 當心網路過濾氣泡 (TED Talk)

3. 文章翻譯自CNN網站,對完整報導有興趣的朋友請參考

http://money.cnn.com/2016/11/09/technology/filter-bubbles-facebook-election/index.html

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