Tuesday, June 10, 2008

You’re not a molecule, but sometimes you’re a statistic

The editorial in the latest issue of Nature, written by me, could in its edited form (my original draft is below) seem to present a capitulation to the view of social science advocated by Steve Fuller at Warwick, who has previously been highly critical of the statistical perspective discussed in my book Critical Mass. (My response to Fuller is here.) But that’s not really how it is. The pull quote (“The goal of social science is not simply to understand how people behave in large groups but to understand what motivates individuals to behave the way they do.”) is equally true in reverse, which is what Fuller seems blind to. I’m more that happy to make explicit what statistical ‘laws’ overlook. But to deny that group behaviour matters, or that it can differ from that predicted by linear extrapolation from individuals, is to deny the ‘social’ in social science, which seems to me a far more egregious oversight.

Fair point from the editor, though: it wouldn’t actually be hard at all to improve on Mill’s words, in the sense of leavening the Victorian stodge. But I hope the editorial doesn’t now seem to be implicitly critical of the González et al. paper that motivated it, on the grounds that it focuses on the masses and not the individual. This paper does reveal information about both. That very issue, however, has provoked an absurd level of hysteria in the wake of the news story we ran. It seems some people who haven’t bothered to read the paper are concerned about privacy. Makes you wonder what they have to hide (not that anyone would be finding out in any case, given that the data were rendered anonymous). Do these people ever stop to think what is happening to the data every time they make a purchase on their credit cards?

******

“Events which in their own nature appear most capricious and uncertain and which in any individual case no attainable degree of knowledge would enable us to foresee, occur, when considerable numbers are taken into account, with a degree of regularity approaching to mathematical.” It would be hard to improve on John Stuart Mill’s words to encapsulate the regularities found in human mobility patterns on page 779 of this issue. Who would have thought that something as seemingly capricious as the matter of where we go during our daily lives could yield such lawfulness?

One of the remarkable features of this work is not the results, however, but the methodology. Social scientists have long struggled with a paucity of hard data about human activities – social networks, say, movement patterns. Self-reporting is notoriously unreliable and labour-intensive. The use, in this case, of mobile phone networks to track individuals has supplied a data set of proportions almost unheard of for such a complex aspect of behaviour: over 16 million ‘hops’ for 100,000 people. The resulting statistics show a strikingly small scatter, giving grounds for confidence in the mathematical laws they disclose.

This adds to the examples of information technologies offering tools to the social scientist that provide a degree of quantification and precision comparable to the so-called ‘hard’ sciences. Community network structures can be derived from, say, email transmissions or automated database searches of scientific collaboration. Online schemes can even enable genuinely experimental study of behaviour in large populations, complete with control groups and tunable parameters.

Making sense of these data sets may require a rather different set of skills from the conventional statistical approaches used in the social sciences, which is why it is no surprise that studies like the present one are often conducted by those trained in the physical sciences, where there is a long tradition of investigating ‘complex systems’ of interacting entities. One view might be that this lends some prescience to the suggestion of sociologist George Lundberg in 1939: “It may be that the next great developments in the social sciences will come not from professed social scientists but from people trained in other fields.” Lundberg was a positivist eager for his field to adopt the methods of the natural sciences.

The ‘physicalization’ of the social sciences needs to be regarded with some caution, however. While some social scientists aim to understand the ways people behave in large groups, others insist that ultimately the goal is not to uncover bare statistical laws and regularities but to gain insight into what motivates individuals to behave the way they do. It is not clear that universal scaling functions can offer that: however vast the data set, the inverse problem of deriving the factors that produce it remains as challenging as ever. Statistical regularities may conjure up images of Adolphe Quetelet’s homme moyen, the ‘average man’ who not only tends to deny the richness of human behaviour but even threatens to impose a stifling behavioural norm.

It would be wrong to imply that the interest of these findings is restricted to the conventional boundaries of the social sciences. Epidemiologists, for instance, have traditionally been forced to work with very simple descriptions of dispersal and contact, for example based on diffusive models, for lack of any hard evidence to the contrary. But recent work has made it very clear that the topology and quantitative details of contact networks can have a qualitative impact on the transmission of disease. There is sure also to be commercial interest in information about patterns of usage for portable electronics, while the nature of mass human movement could inform urban planning and the development of transportation networks.

But for the social sciences proper, the latest results suggest both an opportunity and a challenging question: how much of social behaviour do we capture in statistical regularities, and how much do we overlook?

3 comments:

JimmyGiro said...

Imagine the horror in the corridors of physics departments up and down the land, if they were forced to comply with the edicts of the 'soft' sciences, who point out that physics would become more popular and therefore more economically viable within money-strapped universities, if the subject was more 'touchy-feely'. You can just see the gloating arts faculties, as tears are mopped with corduroy in the quad.

If you can imagine that, then it should be no surprise when the strap-on is on the other codpiece; that social 'scientists' should come up with these rationalized objections at the thought of resulting to maths, just like the 'other lot' do.

Gone are the days of the Michael Polanyi type polymaths, as economics drives science faculties towards 'popularity' rather than rigour.

uhfdf said...

歐美a免費線上看,熊貓貼圖區,ec成人,聊天室080,aaa片免費看短片,dodo豆豆聊天室,一對一電話視訊聊天,自拍圖片集,走光露點,123456免費電影,本土自拍,美女裸體寫真,影片轉檔程式,成人視訊聊天,貼圖俱樂部,辣妹自拍影片,自拍電影免費下載,電話辣妹視訊,情色自拍貼圖,卡通做愛影片下載,日本辣妹自拍全裸,美女裸體模特兒,showlive影音聊天網,日本美女寫真,色情網,台灣自拍貼圖,情色貼圖貼片,百分百成人圖片 ,情色網站,a片網站,ukiss聊天室,卡通成人網,3級女星寫真,080 苗栗人聊天室,成人情色小說,免費成人片觀賞,

傑克論壇,維納斯成人用品,免費漫畫,內衣廣告美女,免費成人影城,a漫,國中女孩寫真自拍照片,ut男同志聊天室,女優,網友自拍,aa片免費看影片,玩美女人短片試看片,草莓論壇,kiss911貼圖片區,免費電影,免費成人,歐美 性感 美女 桌布,視訊交友高雄網,工藤靜香寫真集,金瓶梅免費影片,成人圖片 ,女明星裸體寫真,台灣處女貼圖貼片區,成人小遊戲,布蘭妮貼圖片區,美女視訊聊天,免費情色卡通短片,免費av18禁影片,小高聊天室,小老鼠論壇,免費a長片線上看,真愛love777聊天室,聊天ukiss,情色自拍貼圖,寵物女孩自拍網,免費a片下載,日本情色寫真,美女內衣秀,色情網,

liwo said...

av自拍,臺灣18歲成人免費,avon,正妹強力牆,免費線上成人影片,免費遊戲,a片貼圖,正妹圖片,3d美女圖,杜蕾斯免費a片,蓬萊仙山寫真集,a片網站,哈拉網路成人區,sex女優王國,性感美女,自拍密錄館,18禁卡通,爽翻天成人網,go2av,網拍模特兒應徵,台灣18成人,制服美女,小老鼠成人,成人光碟,金瓶影片交流區,85cc免費影城,成人交友,蓬萊仙山寫真集,無碼,正妹強力牆,嘟嘟情色網,影片轉檔程式,免費成人片觀賞,拓網交友,松島楓免費影片,色美眉部落格,18成人avooo,美腿論壇,辣媽辣妹,露點寫真,哈雷聊天室,18禁影片,看a片,美女工廠,影音城論壇,美女影片,免費遊戲,免費算,小魔女貼影片,a片貼圖,美腿褲襪高跟鞋,av女優王國,觀月雛乃影片,性感美女,

女優王國,免費無碼a片,0800a片區,免費線上遊戲,無名正妹牆,成人圖片,寫真美女,av1688影音娛樂網,dodo豆豆聊天室,網拍模特兒,成人文學,免費試看a片,a片免費看,成人情色小說,美腿絲襪,影片下載,美女a片,人體寫真模特兒,熊貓成人貼,kiss情色,美女遊戲區,104 貼圖區,線上看,aaa片免費看影片,天堂情色,躺伯虎聊天室,洪爺情色網,kiss情色網,貼影區,雄貓貼圖,080苗栗人聊天室,都都成人站,尋夢園聊天室,a片線上觀看,無碼影片,情慾自拍,免費成人片,影音城論壇,情色成人,最新免費線上遊戲,a383影音城,美腿,色情寫真,xxx383成人視訊,視訊交友90739,av女優影片,