Hiddn Tnds in 9 Yas of Havad Businss Rviw Chia-Chi Tsai Chao-Lin Liu Wi-Ji Huang Man-Kwan Shan Dpatmnt of Comput Scinc National Chngchi Univsity, Taipi, Taiwan {99736, chaolin, 1731, mkshan}@nccu.du.tw Abstact In this pap, w dmonstat and discuss sults of ou mining th abstacts of th publications in Havad Businss Rviw btwn 1922 and 2. Tchnius fo computing n-gams, collocations, basic sntimnt analysis, and namd-ntity cognition w mployd to uncov tnds hiddn in th abstacts. W psnt findings about intnational lationships, sntimnt in HBR s abstacts, impotant intnational companis, influntial tchnological invntions, nown sachs in managmnt thois, US psidnts via chonological analyss. Kywods: sntimnt analysis, conomic tnds, txt mining, collocation, tmpoal analysis 1. Intoduction Digital humanitis is an intdisciplinay aa wh sachs mploy computing tchnologis fo th sach and applications of subjcts in humanitis. Rlativly, digital humanitis is a bugoning aa, but thivs apidly in cnt yas [1][]. Digital histoy [2] is a vy impotant fild in digital humanitis. Sto t al. applid imag pocssing tchnius to build th landscap of th Kyoto city and studid th dvlopmnt of th city []. L and L analyzd 3 hundd yas of Koan culinay manuscipts []. Som sachs of Chins histoy hav studid impotant and intsting histoical vnts with th hlp of tchnius of natual languag pocssing (NLP),.g., [1], in th past fw yas. Jin t al. study th concptualization of Chins popl ( 華人, /hua2 n2/) in th modn Chins histoy []. In this pap, w showcas applications of th NLP tchnius to th analysis of a wll-known intnational magazin. W analyzd th abstacts of th aticls publishd in th Havad Businss Rviw [6] (HBR, hncfoth) btwn 1922 and 2. Without th hlp of computing tools, it would not b asy to analyz th contnts of thousands of abstacts and figu out th tnds hiddn in th txt matials. Th abstacts w not public, but bcam availabl to us whn w paticipatd in an activitis that w administd by th Kaggl company 1. In th following psntation and chats, w illustat som statmnts that w not xplicitly offd in HBR. W discovd som hiddn infomation by mining th contnts of th abstacts, with th hlp of NLP tools and som xta data that w 1 http://www.kaggl.com not pat of th HBR abstacts. Th xta data includ a Havad dictionay fo sntimntal wods, which classify wods into positiv and ngativ wods [7], data about th annual GDP gowths of USA [3], and mmbships of th G2 [] and OECD [11] countis. W list th goals of ou xploation in Sction 2, and xplain th mthods fo pocssing th txt matials in Sction 3. indings gading th initial goals w psntd in sval subsctions in Sction. 2. Goals o all issus listd blow, w show som intsting tnds that w hiddn in th HBR abstacts though chats of th annual changs of slctd mtics. W xplod six intsting ustions. 1. Whn USA was mntiond in HBR, what countis of oth gions w mntiond at th sam tim? This povids indicatos fo how USA coopatd with oth countis. W usd comput tools to dtmin whth an aticl discussd issus latd to USA and oth countis. Th counts fo individual countis of a gion,.g., th Asia Pacific gion, a addd fo th gion. 2. Is HBR a CALM piodical? W mployd a Havad dictionay of sntimntal wods (a Havad dictionay of sntimntal wods) to find positiv and ngativ wods in HBR. W studid th annual pcntags of positiv and ngativ wods in HBR aticls. 3. Which and whn impotant lits w mntiond in th HBR abstacts? W studid som nown sachs in managmnt thois and th US psidnts.. HBR offs a window fo watching th impotant companis fo ou livs. W analyzd th annual funcis of slctd companis that w mntiond in HBR abstacts.. HBR also povids a clu fo whn tchnical poducts com into ou livs. By calculating th funcis of som tchnological kywods in HBR, w lookd back on how thos poducts and tchnologis found thi ways into ou livs. 6. Of cous, a good illustation nds a good gaphical psntation. 3. Copus and Mthods Th oiginal data fil is a plain Excl fils. Th fist ow xplains th typs of data in individual columns. Each following ow is an abstact, including th abstact and mta data about th abstact. Th mta data includ th publication dat, th authos, th subjct catgois, tc. o th cunt study, w xtactd th bodis of
th abstacts and savd ach abstact into a fil. Abstacts which w publishd in th sam ya w stod in th sam fold, using th ya as th nam of th fold. Though this pocss, w obtaind 13,22 abstacts which containd 1,36,6 wods. Aft saving th abstacts in folds fo yas, it was asy to comput th funcis of annual funcis of kywods and bigams. Two kywods (a bigam) w considd to appa togth if th sam abstact containd thm. Namly, th collocation window is th whol abstact. W thn plot such chonological data in th illustations. Th analysis of annual funcis of kywods is th sam th Googl Tnd svic 2. Th analysis of n-gams is simila to th Googl Tnd, but consids th co-occuncs of multipl kywods. o histoical studis, th co-occuncs of kywods cay mo pcis smantics and th occuncs of individual kywods. 3 W mployd th Stanfod NLP tools to xtact namd ntitis in th abstacts and to pas th sntncs in th abstacts. Th namd ntitis cognition (oftn fd as NER) task hlps to find nams of countis and companis. Th pasing of sntncs would allow us to conduct dp undstanding of th statmnts. Howv, w hav not compltd ou invstigation in this avnu. W adoptd th Havad motion dictionay to count th funcis of positiv and ngativ wods. It is ctainly possibl to build a classifi to catgoiz th abstacts into positiv and ngativ instancs, but w hav not don so at this momnt.. Th Hiddn Tnds.1 Intnational Rlationships HBR mntiond USA with Euopan and Asian countis mo oftn duing tough tims. igus 1 and igu 2 indicat that, whn USA was discussd, Asia Pacific and Euopan countis w mo funtly mntiond duing Wold Wa II and duing th financial cisis in cnt yas. Ov oth piods, HBR sldom mntiond USA and countis in multipl gion in th sam abstact duing nomal tims. This phnomnon pats whn w study th G2 and th OCED countis. igus 3 and show that Japan and Russia w spcial in that thy w vy impotant fo USA s intsts fo a spcific piod. Thi co-occuncs with USA in HBR btwn 19 and 199 w much mo funt than any oth G2 and OECD countis and vn gions..2 HBR is a Calm Piodical HBR abstacts us positiv and ngativ wods almost constantly ov th yas, ispctivly of th changs of annual GDP changs of USA. Th cuvs in igu show th pcntags of positiv and ngativ wods 2 http://www.googl.com/tnds/ 3 http://nlp.stanfod.du/softwa/ in a ya's abstacts. Th cuv fo th USA GDP shows th ya ov ya chang of GDP. Th pcntags of positiv and ngativ wods vaid within a vy naow ang, in contast of th changs of USA GDP numbs. igu 6 shows th avag numbs of positiv and ngativ wods in an HBR aticl. Th cuvs show that th numbs of wods a incasing slowly. Notic that w did not classify th sntimnt of individual abstacts. In that cas, w must handl th ngation wods o doubl ngations in statmnts. W simply countd th funcis of positiv and ngativ wods at this momnt..3 Elits in HBR W computd th annual funcis of Pt. Duck, Pt M. Sng, John P. Kott, Michal Pot, Gay Haml, Hny Minzbg, Chis Zook, Tom Pts, Nol Tichy, and Godon Donaldson in th abstacts. Whn computing th funcis, w consid a nam with and without th middl nams,.g. w tatd Pt. Duck and Pt Duck as th sam pson. On poblm that w did not solv is that w did not distinguish two psons of th sam nam. If th was an odinay pson whos nam is also Pt Duck and if h was also mntiond in HBR, w would not obtain th coct funcis fo Pt Duck. Pt Duck was th lad in th goup, and statd to b mntiond in HBR sinc 19s. igu 7 shows th annual funcis of th fiv most funtly mntiond sachs sinc 19. W can s that Pt Duck is still th most popula sach, but diffnt sach may bcom popula duing spcific piods. o instanc, Gay Haml was th most btwn 199 and 1991, whn th US conomy was in dpssion. It was intsting fo us to chck whth an abstact would mntion two lits, which may imply that thois of two lits a discussd fo an vnt. Unfotunatly, th most funtly co-mntiond lits took plac only fou tims fo Pt Duck and Pt Sng in 199. Hnc, w do not show a chat fo this xploation. W w intstd in whn HBR mntiond th US psidnts and th chaipsons of th dal Rsv. igu shows th funcis of th US psidnts in HBR sinc 191. Th a six psidnts in this piod. W did not us vy distinguishabl colos fo diffnt psidnts in th chat bcaus th main focus is whn th psidnts w mntiond in HBR. It is intsting fo us to notic that it is th tough tims whn th US psidnts w mntiond in HBR. o instanc, in 197, 19, 21, and cnt yas. Th was a Black Monday in lat 197, th bust of Intnt bubbl aound 21, and global conomic poblms in cnt yas. W did not show a chat fo whn HBR mntiond th chaipsons of th dal Rsv. HBR aly mntiond th chaipsons.
. Wll-Known Companis in HBR igus 9, 1, and 11 dmonstat th appaancs of som big companis in HBR's abstacts. Th vtical bas show th funcis of th nams of th companis in HBR. Appl, Googl, and Samsung a in igu 9. Ths th companis a intacting in multipl snss in cnt yas. HP, IBM, Intl, and Micosoft a in igu 1. od, GE, GM, Blls (including Wstn Elctic, AT&T, and Lucnt) a in igu 11. om igu 1 and 11, w can s how th biths and cycls of iss and falls of som wll-known companis.. Tchnologis in ou Livs Again, th vtical axs of th chats in igus and 13 show th funcis of th tchnological wods in HBR. Computs appa to b th most lasting and influntial poducts fo ou livs so fa. Tlphons and adios w vy old tchnological poducts, as indicatd in igu. igu 13 may mind us th impact of Intnt. Th funcy of "Intnt" dwafs th funcis of oth popula wods..6 An Intactiv Map inally, th visual impact would b gatly stngthnd if w could show th chats with a map. Th map in igu 1 shows th locations of th top 1 most mntiond county nams in HBR duing 199s. You can play with an intactiv vsion at http://cs.nccu.du.tw/~chaolin/map.html.. Concluding Rmaks W applid tchnius fo natual languag pocssing (NLP) to th analysis of th contnts of Havad Businss Rviw. Th sults show that NLP tchnius a pactically usful fo businss infomatics. W bliv that th chats uncovd som intsting 2 1 igu 1. An intactiv map tnds in th HBR abstacts. Howv, a sious sach dos not stop at th point of finding ths intsting tnds. Expts would us th tnds as sds fo futhing invstigation about th past vnts. Hopfully som nw discovis can follow. Acknowldgmnts W thank th valuabl commnts of Pofsso Ming-ng Tsai on this study. Rfncs [1] D. M. By, Undstanding Digital Humanitis, Palgav Macmillan, 2. [2] D. J. Cohn and R. Rosnzwig, Digital Histoy: A Guid to Gathing, Psving, and Psnting th Past ont th Wb, Univsity of Pnnsylvania Pss, 2. [3] GDP: USA GDP btwn 19 and 21: http://www.usgovnmntspnding.com/u s_gdp_histoy#copypast [] G2: G2 majo conomis: http://n.wikipdia.og/wiki/g-2_maj o_conomis [] J. Hsiang (d.), oundations and Imaginations of Digital Humanitis, 211. [6] HBR: Havad Businss Rviw: http://hb.og/ [7] A Havad dictionay of sntimnt wods: http://www.wjh.havad.du/~inui/ spadsht_guid.htm [] G. Jin, W.-Y. Chiu, and C.-L. Liu. uncy analysis and applications of co-occud phass: Th oigin of th "Hua-Rn" concpt as an xampl ( 共現 詞頻分析及其運用 以 華人 觀念起源為例 ), Sis on Digital Humanitis, J. Hsiang (d.), 3, 2. (in Chins) [9] K. L and J.-y. L, Quantitativ analysis of th 17th-19th cntuy Koan culinay manuscipts, in [], J. Hsiang (d.), 19 2, 2. [1] C.-L. Liu, G. Jin., Q. Liu., W.-Y. Chiu., and Y.-S. Yu. Som chancs and challngs in applying languag tchnologis to histoical studis in Chins, Intnational Jounal of Computational Linguistics and Chins Languag Pocssing,, 211. [11] OECE: Oganisation fo Economic Co-opation and Dvlopmnt (OECD): http://www.ocd.og [] T. Sto, T. Iizuka, A. Matsumoto, T. Kiimua, K. Yano, T. Nakaya, and Y. Isoda, Tansition of uban landscap with Kyo-machiya in vitual Kyoto, Digital Humanitis: Nw Appoachs to Histoical Studis, J. Hsiang (d.), 2. Amica Euop 1 192 192 193 193 19 19 19 19 196 196 197 197 19 19 199 199 2 2 21 21 igu 1. Annual funcy of USA bing mntiond with G2 countis in th gions
2 2 1 Amica Eupo 1 192 192 193 193 19 19 19 19 196 196 197 197 19 19 199 199 2 2 21 21 igu 2. Annual funcy of USA bing mntiond with OECD countis in th gions 13 9 Amica Euop Russia Japan 192 192 193 193 19 19 19 19 196 196 197 197 19 19 199 199 2 2 21 21 igu 3. Annual funcy of USA bing mntiond with Russia, Japan, and G2 countis 13 9 Amica Eupo Russia Japan 192 192 193 193 19 19 19 19 196 196 197 197 19 19 199 199 2 2 21 21 igu. Annual funcy of USA bing mntiond with Russia, Japan, and OECD countis P c n t 2 % of positiv wods % of ngativ wods yoy GDP gowth (%) 192 193 19 19 196 197 19 199 2 21 Yas - igu. Sntimnt of HBR mains lativly stabl ispctiv of USA GDP gowth
2 2 1 1 pos-p-at ng-p-at 192 193 19 19 196 197 19 199 2 21 igu 6. Numbs of positiv/ngativ wods p aticl changd gadually 1 1 6 2 Pt. Duck Gay Haml Hny Mintzbg John P. Kott Michal Pot 19 192 19 196 19 199 1992 199 1996 199 2 22 2 26 2 21 igu 7. amous sachs in managmnt thois 3 2 1 Jimmy Cat Ronald Ragan Gog Bush Bill Clinton Gog W. Bush Baack Obama 191 196 1991 1996 21 26 211 igu. Whn HBR mntiond US Psidnts 2 1 1 Appl Googl Samsung 197 19 19 199 199 2 2 21 21 igu 9. Whn som companis statd to intact
IBM HP Micosoft Intl 19 19 19 19 196 196 197 197 19 19 199 199 2 2 21 21 igu 1. Whn som modn companis took th stag 1 od 1 GM GE 1 Blls 6 2 192 192 193 193 19 19 19 19 196 196 197 197 19 19 199 199 2 2 21 21 igu 11. Cycls of som hundd-ya old companis 32 2 adio tlvision tlphon comput -commc 192 192 193 193 19 19 19 19 196 196 197 197 19 19 199 199 2 2 21 21 igu. Som modn tchnologis in ou livs 13 9 adio tlvision tlphon comput intnt -commc 192 192 193 193 19 19 19 19 196 196 197 197 19 19 199 199 2 2 21 21 igu 13. intnt is dominating