根據波利安娜的原則，70年代由兩個社會心理學家制定，人們往往比負面(miàn)的人更頻繁地使用積極的話。此外，我們傾向(xiàng)于更詳細地記住，更詳盡地描述那些具有積極而不是消極關聯的記憶。
According to the Pollyanna principle, formulated in the ‘70s by two social psychologists, people tend to use positive words more frequently than negative ones. Furthermore, we tend to remember in greater detail and describe more exhaustively those memories with a positive rather than a negative association. 根據這一原則，美國佛蒙特大學的研究人員試圖揭示出最頻繁發生的語言。結果？世界上最幸福的語言是... 西班牙語，緊随其後的是葡萄牙語。最不利的是中國人。 Based on this principle, researchers at the University of Vermont in the U.S. attempted to reveal in which language this happened most frequently. The result? The happiest language in the world is… Spanish, closely followed by Portuguese. The least positive ended up being Chinese. 爲了得出結論，他們在Twitter上搜索了十萬種最常用的單詞，在世界上最流行的10種語言的電影字幕，報紙和歌曲中。然後，研究人員每個語言地點有50位母語，每個單詞按照它們産生的情緒，按比例。除了排名的結果之外，波利安娜原則在每種語言的情況下都(dōu)被(bèi)證明：我們使用比否定詞更好(hǎo)的詞語，不管我們說什麽語言。例如，就(jiù)西班牙語而言，每九個正面(miàn)詞都(dōu)使用一個負面(miàn)詞彙。在中文方面(miàn)，最不樂觀的語言，可以這麽說，比例還是以70/30的比例贊成(chéng)積極的話。 To reach their conclusions, they searched for 100,000 of the most-used words on Twitter, in movie subtitles, newspapers and songs of the 10 most-spoken languages in the world. Then the researchers had 50 native speakers of each language place each word on a scale according to the emotion it produced in them. Beyond the results of the ranking, the Pollyanna principle was proven in the case of each language: we use more positive words than negative ones, regardless of the language we speak. In the case of Spanish, for example, one negative word is used for every nine positive ones. In Chinese, the least-optimistic language, so to speak, the proportion still favors positive words at a rate of 70/30. 佛蒙特大學的團隊根據Twitter的要求開始了這個項目，其目的是能(néng)夠盡可能(néng)精确地測量社交網絡上發布的每個推文的積極性或消極性。研究人員已經獲得了英文的這些結果，他們希望能(néng)夠很快將(jiāng)其應用于其餘的語言。 The team at the University of Vermont started on this project at the request of Twitter, whose intention is to be able to measure, with the greatest exactitude possible, the positivity or negativity of each tweet posted on the social network. The researchers had already obtained these results for the English language, and they hope to be able to apply this “happiness meter” to the remaining languages very soon. 上一篇:怎樣的譯員容易失去市場？ 下一篇
