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如何科学地获得成功?
热度 1 wshuyi 2019-12-13 15:19
给你推荐一本“武器级”图书。 尴尬 昨天晚上,我读完了一本书的最后一页。感触良多,于是发了一个朋友圈。 好久没有这么畅快淋漓读完一本纸质书了。我带着它去了外地开会,用其中的内容作为工具,帮我观察分析整个儿学术会议的进程和途中见闻。书中的真知和洞见让我时而豁然开朗,时而如芒在背。古人说,朝闻道,夕死可矣。我却想说,如果10年前能读过这本书,那该有多好啊。 有朋友留言,问书名。 我原以为也就有三五个人感兴趣,打算私信分享一下。结果被涌进来的询问弄懵了。 公开留言,答复给所有人? 不行。 因为这本书的书名,可能会引起误会,导致别人对我的智商产生怀疑。那就很尴尬了。 可我没有时间一一私信说明,也不可能在朋友圈留言里作出详细解释。 所以,想了想,还是写篇文章吧。除了平息朋友们被我晾了一整天的愤怒,更是要把 这本书 ,也推荐给你。 误解 这本书的名字,叫做 《巴拉巴西成功定律》 。 明白我的烦恼根源了吧? 一提起这“成功”两个字,你可能会嗤之以鼻: 王老师,你怎么也开始推荐烂俗的成功学了? 别误会,那些机场店里面给你打鸡血的书,我是不会推荐的。为了赚那点小钱,就把自己的信誉全都赔进去,犯不上。 这本书的名字,比较容易引起误会,但是它实际上探讨的,并不是什么“成功的捷径”,而是“成功的科学”(The Science of Success)。 你可能觉得,这不是一回事儿吗? 完全不一样。 在科学视角下,成功学根本难以立足。原因至少包括3点: 样本数量太小 缺乏因果分析 缺乏后续验证 拿着一个别人成功的案例,不考虑年代,不考虑背景信息,不考虑主人公的天赋和特质,就武断做出结论,说成功就是因为某个因素造成的。甚至有时候,还拿当事人自己的叙述来断章取义,显然不靠谱。 但是提出某种“导致成功的因素”后,作者往往会非常兴奋地告诉你: 看,这是成功的捷径。你照着走吧,准没错! 你照着走,于是成功就出现了。 别想多了,不是你成功了。是 卖你书的人 成功了。 你买他的书,听他的讲座,为他的财务自由添砖加瓦,贡献良多。 信“成功学”家,还不如信股评家。至少,人家还弄个技术分析图啥的,看着很有科技感。一样是赔钱,这样赔,至少更有面子。 那成功的科学指的是什么? 非常硬核。 它的基础,不是什么当事人追忆往昔的激情描述,而是一连串客观记录的行为数据。例如一场场体育比赛里面的成绩,一次次拍卖会上的艺术作品价格,一回回权威期刊上的发表记录…… 这些数据,更贴近真实,更难以伪造。 而这些信息的汇聚和分析结果,将可以给我们展现“成功”原来是 有规律的 。 规律 成功真的有规律吗? 听到这里,你又该狐疑了。 王老师鼓吹成功有规律,怎么听着还是给成功学站台呢? 我曾经在课程的《时间管理》章节,给学生们列出成功公式。 用翻页器,我把下面的文字一行行展示。 成功的要素包括: 1分的天才 9分的努力 学生们很不屑,心说“又是让我们好好用功的那老一套”。 我顿了一下,然后告诉他们,我还没说完。 接着按动翻页器,展示完这个幻灯的最后一项: 1分的天才 9分的努力 90分的运气 他们笑了,表示这才对嘛。 我跟着一起笑。 在生活中,我们都不难观察到这种有意思的结果,但是不知道如何解释——拥有几乎同样的天赋,付出近乎相同的努力,某些人获得了巨大成功,其他人却败得一塌涂地。 于是,我们把这些不可解释因素,统统装进了“运气”这个大筐里面,就算了事儿,面对成败处之泰然,甚至“佛系”。 但是,看完了这本书,再想想上面的公式,我突然就笑不出来了。 原来,这才叫做“内行看门道,外行看热闹”。 我们这些外行,在大学课堂上,揶揄了很多偷偷掌握成功规律奥秘的人。 想想都脸红。 原来,通往成功的道路上,所谓的不可解释部分,只是我们研究的功夫下得不够,见识过于浅薄罢了。 洞察 这本书的作者,是美国东北大学(Northeastern University, Boston)教授巴拉巴西( Albert-László Barabási )。 这家伙的特点,是经常到期刊上灌水(发大量论文)。 在学术圈里混久了,对发论文这事儿,一点儿不觉得新鲜。许多名家,一介绍就是“发表论文数百篇”。真不知道人家是怎么把喝咖啡的时间都省出来写论文的。 稍有区别的是, 巴拉巴西灌水的期刊,主要是 Science 或者 Nature 这一级别的。 根据目前我国多所高校的科研成果奖励政策,在这两种刊物上发表一篇文章,奖金都在百万级别。 所以,你说巴拉巴西教授算不算成功的学者? 他不仅高水平论文数量多,同时还是一位 畅销书作家 。 巴拉巴西之前的两本书,《爆发》和《链接》,都是畅销全球。 这样的人,花费了数年的时间,牺牲了许多陪伴家人的机会,写出来的新书,会是什么样子呢? 答案是: 强烈冲击你的认知。 想想看: 一幅图画的价值,究竟如何判定? 靠着买粉丝、雇水军,能否让你的影响力脱颖而出? 怎样才能在众筹网站上获得足够的支持? 一篇论文多个作者署名,功劳该归谁? 出名是不是一定要趁早? 爱因斯坦为大众熟知,是因为什么? 当你通过思考,有了自己的答案后,跟书里的讲解对比一下,你就会发现——之前你根据常识与经验得出的结论,原来许多都是错的。 这就是为什么,我会在朋友圈发出本文开头那样的感慨。 武器 根据你自己的喜好,以及你是否想让别人来阅读,书可以分成4种。 第一种,你不喜欢读,也不希望别人阅读。例如那些包含不良信息的书。 第二种,你不喜欢读,却希望别人阅读。例如员工守则。 第三种,你喜欢读,也希望别人阅读。例如武侠科幻等流行作品。因为这样可以构建共识,寻找共同感兴趣的话题。 第四种,你喜欢读,却不希望别人阅读。这种书,我把它称为“武器级别”。 这种书的特点,在于启迪心智的同时,还能给你行之有效的方法论。普通人读完了,就会比没有读过的人具有信息、知识、乃至实践层级的优势。 它就像是机关枪。普通人稍加训练,就很容易掌握。而一旦掌握了,就会在竞争中处于显著优势地位。 1893年,50名英军,就是用5挺马克沁机关枪,击败了5000人的军队,造成对方1500人死伤。你说武器优势重要不? 在今天这样一个竞争广泛存在的年代,你应该主动寻找这第四种书,并且认真阅读。否则,你就是在参加一场不公平的竞争,而你,恰恰是处于劣势的一方。 我给你推荐的这本 《巴拉巴西成功定律》 ,恰恰就属于这一类。 当别人都把成功看做运气带来的偶然事件时,如果你早早了解到了无数领域中成功的共性和特性,并且充分利用它们,那么你就像是在大航海时代拥有了高超的定位技术。 虽然,这无法保证你不会遭遇狂风巨浪的侵袭,但比起那些在茫茫大海中都不知道自己身处何地的船长和水手们来说,你的成功概率要大不知多少倍。 祝阅读愉快! 读过本文,如果觉得有收获,请 点赞 。 要读更多的文章,微信关注我的公众号 “玉树芝兰”(nkwangshuyi) 。别忘了 加星标 ,以免错过新推送提示。 如果本文对你身边的亲友有帮助,也欢迎你把本文通过微博或朋友圈分享给他们。 延伸阅读 你可能也会对以下话题感兴趣。点击链接就可以查看。 如何用虚拟现实培训领导力? 你需要补哪些核心能力? 写给我即将毕业的研究生 你打算找一份稳定的工作? 创新怎么教? 题图: Photo by Nghia Le on Unsplash
4189 次阅读|2 个评论
Phsic Toady :Q&A: Albert-László Barabási on the diversity
zguodong2006 2017-4-26 09:46
QA: Albert-László Barabási on the diversity of networks The author of Network Science talks about his foundational work in that field and developing resources for online learning. SHARES Network science is a new and rapidly growing field, with applications ranging from protein interactions to the internet. However, the sheer breadth of areas in which network analysis might be useful presents a daunting challenge to potential textbook authors. In Network Science (Cambridge University Press, 2016), Albert-László Barabási tackles that challenge. The result, writes reviewer Zoltán Toroczkai in the April issue of Physics Today, is “a hands-on and engaging textbook” that also makes good use of accompanying online resources, such as animations and other pedagogical tools. Albert-Laszlo Barabasi. Photo by Gabor de Fiala. Albert-László Barabási. Credit: Gabor de Fiala Physics Today recently talked to Barabási about his pioneering contributions to network science, the challenges of writing a textbook in an interdisciplinary field, and his approach to developing online resources. PT: How did you become interested in networks as a field of study? BARAB?SI: In 1994, after starting my postdoc in the theoretical physics division at the IBM Watson Research Center, I became curious about what IBM does, and I began reading about the fundamentals of computer science. It was in this context that I encountered networks. I realized that traditional models assume that real networks are randomly wired, even though they could hardly function if that were the case. So I started working on networks, bringing a statistical physics perspective to them. I published my first paper on networks in Physical Review Letters in 1996. It focused on a boring network, a lattice, but it got me started. I also wrote another paper, more in the spirit of what we call network science today, that I simply could not get published. It was rejected by four physics journals, and not because the referees found anything wrong with it. Instead, they kept wondering, “Why do we care?” It wasn’t until 1999 that we network science researchers could finally get our papers published. PT: Network Science contains incredibly diverse examples of networks, including power grids, social media, guests at a party, and airport congestion. How did you approach the challenge of writing a textbook on a field that is so interdisciplinary and has such wide-ranging applications? BARAB?SI: The challenge preceded the book writing—I encountered it while preparing a class that I had originally designed for physicists. The audience expanded, and more and more computer science, biology, and economics students started to attend. With that shift, the examples expanded. The course evolved by acquiring more interdisciplinary examples and applications while maintaining its statistical physics–inspired core. In writing the book I faced another challenge: How do I make it accessible to both undergraduate and graduate students? In the end, I achieved that by focusing in the main text on the conceptual questions and the key results, and delegating the more involved derivations and analytical issues to sections on “Advanced Topics” that are geared toward graduate students. PT: One of your most famous contributions to network science has been the concept of scale-free networks. What is a scale-free network, and why might that attribute be significant? BARAB?SI: In scale-free networks the degree distribution, which captures the number of links for each node, follows a power law. This is in contrast with random networks, in which the distribution of links follows a Poisson form. Scale-free networks are significant for two reasons. The first is that the power law allows for hubs, which are nodes with an exceptional number of links. Once such hubs are present, they fundamentally change the system’s behavior—they are very effective at spreading viruses, for example—or confer robustness to the network. The second reason is universality: While we discovered scale-free networks in the context of the World Wide Web, subsequently researchers found that most biological, technological, and social networks are in fact scale-free. That includes the protein interaction networks in our cells, the infrastructure of the internet, and social networks like Facebook and Twitter. PT: Network Science has a number of online resources associated with it, including teaching resources, animations, and a Facebook page. How did you design and develop those online components, and what do you think they add to the book? BARAB?SI: The book was designed to be a textbook; hence it was natural that I share the resources I use teaching it, from videos to slides, to make it easy for instructors who would like to take up the subject. At the same time, there are so many fantastic videos and interactive features that illuminate the properties of networks and their applications that I felt it would be a shame not to offer them to students. The online resources were the best way to achieve that. And we plan to expand it further: Soon we will start posting the translations in several languages, from Russian to Spanish, to expand the pool of students and instructors who can benefit from the book. PT: What are you currently reading? BARAB?SI: Seventh Sense, by Joshua Cooper Ramo, which exposes the power of networks in politics and business. PT: What is your next project? BARAB?SI: I am working on a general audience book titled The Formula: The Quantitative Science of Success, which unveils the relationship between performance and success in the era of big data. There is a simple fact at its heart: Performance is what we do, but success is what our community and environment do to us, by appreciating―or ignoring―our performance. It will discuss scientific success as well: When does a breakthrough happen in the life of scientists? And what are the network and societal forces that pull some discoveries or scientists into the limelight yet ignore other, equally novel and innovative efforts? Once the book is finalized, I hope to return to the Network Science textbook and add two or three more chapters on topics that I did not have the energy to cover in the first edition, like weighted networks, spatial networks, and network biology.
个人分类: 学术名家|1184 次阅读|0 个评论
喜读巴拉巴西的第一部网络科学专著:感想(1)
热度 1 Fangjinqin 2015-10-14 09:50
喜读巴拉巴西的第一部网络科学专著 感想(1) 国际上网络科学的领军人物之首巴拉巴西教授经过20年的拼搏,我终于喜读到2015年他正式出版个人第一本网络方面的专著《网络科学》(共有十章,还有引言和前言),该书图文并茂,系统全面,具有权威性,值得一读!它为此前10年出版的二部网络科学的科普名作《链接》和《爆发》注入更大魅力,翻开了网络科学史册新的一页。 众所周知, 1999 年10月美国圣母大学物理学教授巴拉巴西及其博士生阿尔伯达,在美国《科学》上发表了题为“随机网络中标度的涌现”的论文,发现了无尺度网络,一举成名。但是,科学史上任何发现都不是一帆风顺的,无尺度网络的发现同样充满了艰难曲折的道路。 自然,巴拉巴西自己的的经历就是最好代表和见证。在这个专著《网络科学》中,他自述了许多真实的故事,特别是透露了他经历的五次经历的失败经验教训:例如,他不仅有3篇网络论文(1995,1996,1998))曾经被拒发表,还有一次映射网络的探索失败(1996);而且因开始无尺度特性缺乏确切的数学证明被人体特别是数学家讽刺挖苦,导致他在1999申请美国国家基金和美国国防部项目都失败了。他的书的引起里序举了五次失败的具体情况,其 当然,更有他与学生合作的关于无尺度网络首篇开拓性论文投稿给《科学》杂志,一开始就被拒的难忘故事。但是,不论多少次挫折失败都没有使他丧失斗志。他的顽强抗争终于成功了。他们的论文“随机网络中的标度涌现”终于在1999年美国顶级《科学》杂志上发表了,从此一举成名,他与小世界网络的发现并举揭开网络科学的诞生的序幕。 巴拉巴西 的经验教训非常值得 我们 吸取,中国一些学者包括院士在内,往往缺乏那种坚持抗争的精神,使得一些创新成果在国际顶级刊物失之交臂。 因为涉及知识产权问题,暂时不便在此转载。有兴趣者想法去购买或咨询相关信息。 先让我们看一看新书的扉页和引言封面,一睹为快。
个人分类: 杂谈评论|5145 次阅读|2 个评论
巴拉巴西教授可以正式招收网络科学研究方向的博士生了
热度 2 babyann519 2014-3-2 02:35
2014年2月24日 东北大学授予巴拉巴西教授 Robert Gray Dodge Professorship in Network Science,据说是该校最高荣誉~ Event Timeline 3:00-3:10 PM Dean Murray Gibson delivers welcome remarks, introduces Gene Stanley, William Fairfield Warren Distinguished Professor at Boston University, and then sits back in audience. 3:10-3:15 PM Gene Stanley comes to podium and will say a few words about Professor Barabasi. When he is done speaking, he will sit back in the audience. 3:15-3:20 PM Dean Larry Finkelstein comes to podium, introduces Professor Barabasi (career highlights, achievements) and prefaces his inaugural lecture, titled “Science of Success” and then sits back in audience. 3:20-4:00 PM Professor Barabasi steps up to the podium to deliver his inaugural lecture (35-40 minutes). 4:00 Professor Barabasi concludes his lecture and begins QA session from the podium. Two hand held mikes will circulate in the audience and will be managed by event staff. 4:15 PM QA concludes 4:20 PM Dean Gibson and Dean Finkelstein step to the podium. Dean Gibson introduces Provost Director for the installation. Provost: It is now time to formally install Albert-Laszlo Barabasi as the holder of the Robert Gray Dodge Professorship in Network Science. President Aoun, it is my privilege, along with Dean Gibson and Dean Finkelstein, to present to you Albert-Laszlo Barabasi for investiture in the Robert Gray Dodge Professorship in Network Science. Provost: Professor Barabasi, will you please come forward? Provost: On behalf of the Board of Trustees and the faculty of Northeastern University, I am pleased to formally invest you in the Robert Gray Dodge Professorship in Network Science. [Applause and photo ops: 1—Provost presenting medallion to Barabasi, 2—Provost Director, Dean Gibson, Dean Finkelstein, and Professor Barabasi. 4:25 PM Dean Gibson invites Professor Barabasi to the podium for a brief “thank you.” (1-2 minutes). Then Provost Director, Dean Gibson, and Barabasi take their seats in audience 4:30 PM Dean Finkelstein invites President Aoun to the podium for remarks. Dean Finkelstein takes seat in audience. President Aoun delivers remarks. (2-3 minutes) 4:35 PM Dean Finkelstein returns to the podium and thanks guests for attending and invites everyone to the reception in the Visitor Center. 4:35 PM Reception in Visitor Center begins.
个人分类: 海边拾贝|6956 次阅读|3 个评论

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