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從賈斯汀?比伯到數(shù)據(jù)學家,Twitter何以成為一門顯學

從賈斯汀?比伯到數(shù)據(jù)學家,Twitter何以成為一門顯學

Erika Fry 2014年09月01日
自Twitter創(chuàng)建以來,各路學者紛紛涌向這一微博平臺,不是去發(fā)帖,而是去從事研究工作。在學術界看來,Twitter擁有最為豐富,也許是前所未有的數(shù)據(jù)集。它就相當于一個實時數(shù)據(jù)的虛擬培養(yǎng)皿,吸引著各個學科的學者開展五花八門的研究。

????這個故事的開篇距現(xiàn)在并不遙遠,最初的主角是計算機科學家。相較于大多數(shù)學者,數(shù)據(jù)對于計算機科學家甚至更為重要——多年來,他們一直在挖掘他們各種稀奇古怪的數(shù)據(jù)集。例如,安然公司(Enron)的電郵【大約600,000條訊息,分屬于158名安然雇員,美國聯(lián)邦能源監(jiān)管委員會(Federal Energy Regulatory Commission)在結束對安然公司的調(diào)查后將其公布于眾】于2003年公布后,就成為該領域的流行素材。

????看上去,社交媒體顯然是學者們挖掘數(shù)據(jù)的下一個前沿陣地,但在2003年,當計算機科學家詹妮弗?戈爾貝克受到MySpace啟示,首次開始研究這些社交平臺時,人們并不認為這些研究是有前途,或嚴肅的工作。她的高科技領域同事將這一研究嗤之為“社交科學”;而在社交網(wǎng)絡的萌芽階段,規(guī)模最大的網(wǎng)站是擁有兩千萬會員的成人交友網(wǎng)站AdultFriendFinder。

????作為一名博士研究生,戈爾貝克看到了此類平臺中蘊含的巨大潛力。她說:“在這些平臺上可以做大量有趣的計算工作”。然而,甚至當她在2005年拿到學位的時候,她依然沒有說服計算機科學系認同這種觀點。

????現(xiàn)如今,已經(jīng)成為馬里蘭州大學帕克分校(University of Maryland, College Park)教授,并兼任人機互動實驗室負責人的戈爾貝克,繼續(xù)利用社交媒體研究人和人際關系。她的著述頗豐,曾以“YouTube上的社區(qū)感與社區(qū)結構”、國會議員如何使用Twitter、以及人與寵物關系等主題發(fā)表論文。而使她尤其受到追捧的是她在TED大會上的發(fā)言:《扭扭薯條謎題:社交媒體點贊泄露的信息超乎你想象的原因何在》,自2013年10月以來,該視頻的觀看次數(shù)已經(jīng)多達120萬次。

????另一名先驅(qū)是密歇根州大學(University of Michigan)信息與計算機科學助理教授埃伊坦?阿達爾。數(shù)年前,他利用博客來研究模因的蔓延機制,2007年,他參與創(chuàng)立了“網(wǎng)絡博客與社交媒體國際大會”(International Conference on Weblogs and Social Media),其目的是為從事類似工作的研究者建立一個生態(tài)圈。同年的活動吸引了145人參與,大會主題包括《在公司博客上建立信任》和《Flickr上的社交探索》等等,其主旨演講人埃文?威廉姆斯不是別人,正是當時羽翼未豐的Twitter公司的創(chuàng)始人。

????研究Twitter的首批學者,往往是像戈爾貝克和阿達爾這樣的計算機科學家,他們既懂Twitter,同時也具備收集并處理數(shù)據(jù)的技術。此外,首批學者中還包括對網(wǎng)絡效應特別感興趣的物理學家以及信息科學和通訊學者。早期的研究往往以Twitter為中心,對該服務的使用方式和目的進行統(tǒng)計分析。然后出現(xiàn)了一些更復雜的研究,其重點是研究Twitter的機制:比如“取消關注的動態(tài)情況”、“瞬時群體發(fā)現(xiàn)”、或者“Twitter主題內(nèi)用戶及消息集群的模式”。新加入研究大軍的人多為埃默里這樣的社會科學家,他們提出了數(shù)據(jù)應用的構想,比如預測選舉的結果,或者闡明Twitter大學年齡用戶自戀情節(jié)。但這些人往往并不是收集和處理數(shù)據(jù)的行家里手。(正因如此,大量跨學科研究工作層出不窮,戈爾貝克的實驗室就從事類似研究)。

????研究報告《人們研究Twitter時是在研究什么?》指出,專注于Twitter的論文數(shù)量在2007年有3篇,2008年增加到了8篇,2009年增加到了36篇,此后便一路顯著上升。

????The story begins in the not-too-distant past with computer scientists. Even more than most academics, computer scientists need data—and for years, they’ve mined whatever odd and interesting datasets have come their way. The Enron emails—the 600,000 some messages belonging to 158 Enron employees and made public by the Federal Energy Regulatory Commission after its investigation of the company—became popular fodder in the field, for example, after they were released in 2003.

????Social media may seem an obvious next frontier for data-minded academics, but when computer scientist Jennifer Golbeck first started studying such platforms in 2003 (she was inspired by MySpace), it was not considered particularly promising or serious work. Colleagues in her highly technical field dismissed it as “social science”; and in the nascent universe of online social networks, the largest was a hook-up site with a community of 20 million members called AdultFriendFinder.

????Golbeck, a Ph.D. student at the time, saw greater potential in such platforms: “There was so much interesting computing to be done,” she says. But she was still battling to convince computer science departments of this when she completed her degree in 2005.

????Now a professor at University of Maryland, College Park, Golbeck heads up the school’s Human-Computer Interaction Lab and continues to study what can be learned about humans and relationships using social media. Her prolific output has included papers on “the sense and structure of community on YouTube,” how Congressional representatives use Twitter, and the dynamics of the human-pet relationship (many platforms). That work makes her much in demand—her TED talk, “The Curly Fries Conundrum: Why social media likes say more than you might think,” has been viewed 1.2 million times since October 2013.

????Eytan Adar, now an assistant professor of information and computer science at the University of Michigan was another pioneer. Years ago he used blogs to study how memes spread and, in 2007, he co-founded the International Conference on Weblogs and Social Media in an effort to build community among researchers doing similar work. That year, the event drew 145 people, offered talks like “Building Trust on Corporate Blogs” and “Social Browsing on Flickr,” and featured Ev Williams, the founder of a then-fledgling start-up called Twitter, as the keynote speaker. (Like Twitter, the conference has grown a lot since then.)

????The first academics to study Twitter tended to be computer scientists like Golbeck and Adar, who had both the savvy to understand Twitter and the tech skills to collect and manipulate its data, as well as physicists and information science and communications scholars who were particularly interested in network effects. Research from those early years tended to focus on Twitter—statistical analyses of how and for what the service was used. Then came more sophisticated studies focused on the mechanics of Twitter: the study of things like “unfollow dynamics,” “transient crowd discovery,” or “patterns in Twitter intra-topic user and message clustering.” Later to the party were social scientists, like Emery, who dreamt up applications for the data—predicting the outcome of elections, for instance, or elucidating the narcissism of Twitter’s college-aged users—but tended to be less technically adept at collecting and manipulating it. (As a result, a number of interdisciplinary research efforts—like those that take place in Golbeck’s lab—have sprung up.)

????According to the study, “What do people study when they study Twitter?,” the number of Twitter-focused papers has grown from 3 in 2007, to 8 in 2008, to 36 in 2009, and is up considerably since then.

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