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15 語数: 398 語 出題校 法政大 5 We are already aware that our every move online is tracked and analyzed. But you 2-53 couldn't have known how much Facebook can learn about you from the smallest of social interactions - a 'like'*. (1) Researchers from the University of Cambridge designed (2) a simple machine-learning 2-54 system to predict Facebook users' personal information based solely on which pages they had liked. E "We were completely surprised by the accuracy of the predictions," says Michael 2-55 Kosinski, lead researcher of the project. Kosinski and colleagues built the system by scanning likes for a sample of 58,000 volunteers, and matching them up with other 10 profile details such as age, gender, and relationship status. They also matched up those likes with the results of personality and intelligence tests the volunteers had taken. The team then used their model to make predictions about other volunteers, based solely on their likes. The system can distinguish between the profiles of black and white Facebook users, 15 getting it right 95 percent of the time. It was also 90 percent accurate in separating males and females, Democrats and Republicans. Personality traits like openness and intelligence were also estimated based on likes, and were as accurate in some areas as a standard personality test designed for the task. Mixing what a user likes with many kinds of other data from their real-life activities could improve these predictions even more. 20 Voting records, utility bills and marriage records are already being added to Facebook's database, where they are easier to analyze. Facebook recently partnered with offline data companies, which all collect this kind of information. This move will allow even deeper insights into the behavior of the web users. 25 30 (3) - Sarah Downey, a lawyer and analyst with a privacy technology company, foresees insurers using the information gained by Facebook to help them identify risky customers, and perhaps charge them with higher fees. But there are potential benefits for users, too. Kosinski suggests that Facebook could end up as an online locker for your personal information, releasing your profiles at your command to help you with career planning. Downey says the research is the first solid example of the kinds of insights that can be made through Facebook. "This study is a great example of how the little things you do online show so much about you,” she says. "You might not remember liking things, " but Facebook remembers and (4) it all adds up.", * a 'like': フェイスブック上で個人の好みを表示する機能。 日本語版のフェイスブックでは「いいね!」 と表記される。 2-56 2-57 2-58 36

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経営経済学 大学生・専門学校生・社会人

ピグー効果という例外を除いたとして、 単純に「貨幣市場が流動性のわなに陥っている場合には、物価の下落によって実質貨幣供給量が増加してもそれが国民所得の増加をもたらさないので、総需要曲線は垂直となる。」理由を教えてほしいです。

Ⅰ 【問題22-2】 国民所得と物価水準の関係を表す総需要曲線と総供給曲線に関する次の記 述のうち, 最も妥当なのはどれか。 1. 政府支出の増加は, IS曲線の右上方へのシフトを通じて総需要曲線を右 Movie 145 上方へシフトさせるが, 総需要の増加に対応して生産が拡大するので総供給曲線を右 下方へシフトさせることになる。 ! 2. 貨幣市場が流動性のわなに陥っている場合には、 ピグー効果が働かないとすれば 物 価の下落によって実質貨幣供給量が増加してもそれが国民所得の増加をもたらさない ので,総需要曲線は垂直となる。 ! 3. 総供給曲線の傾きは投資の利子弾力性の大きさによって決定され, 利子弾力性がゼロ! の場合には,総供給曲線は垂直になり, 弾力性が無限大の場合には水平となる。 4. 貨幣供給量の増加は、物価の上昇を通じて総供給曲線を左上方にシフトさせるだけで なく,利子率の低下を通じて投資を増加させるので,総需要曲線を右上方へとシフト させる。 5. 貨幣賃金が上昇する場合には,労働供給量の増加により生産が拡大するので,総供給 曲線は右下方にシフトするが, 賃金上昇が消費需要を拡大させるので、総需要曲線は 右上方にシフトすることになる。 (国家Ⅱ種)

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