一般社団法人 電子情報通信学会
ిࢠ৘ใ௨৴ֶձTHEࣾஂ๏ਓINSTITUTE
OF ELECTRONICS,THE INSTITUTE OF ELECTRONICS,INFORMATIONAND COMMUNICATION ENGINEERS

信学技報
৴ֶٕใ
IEICE Technical Report
TECHNICAL REPORT OF IEICE.

NLC2015-49 (2016-02)

INFORMATION AND COMMUNICATION ENGINEERS

ϨϏϡʔ෼ੳʹ͓͚Δ೔தؒͷධՁͷࠩҟ‫ݕ‬ग़Ԧશ†ౢా ࿨޹††† ‫۝‬भ޻‫ۀ‬େֶେֶӃ ৘ใ޻ֶ෎ ઌ୺৘ใ޻ֶઐ߈†† ‫۝‬भ޻‫ۀ‬େֶେֶӃ େֶӃ৘ใ޻ֶ‫ڀݚ‬Ӄ ஌ೳ৘ใ޻ֶ‫ܥڀݚ‬
˟ 820–8502 ෱Ԭ‫ݝ‬൧௩ࢢ઒௡ 680-4
E-mail: †{q wang,shimada}@pluto.ai.kyutech.ac.jp͋Β·ۙ͠೥ɼΠϯλʔωοτͷී‫ʹٴ‬൐͍ɼ WEB ্ʹ͸঎඼΍αʔϏεʹର͢Δଟ͘ͷධ൑৘ใ͕஝ੵ͞Ε͍ͯΔɽ͜ΕΒͷ৘ใΛ෼ੳ͢Δ͜ͱ͸ɼϢʔβʔʹͱͬͯ঎඼ͷબ୒ʹ͍ͭͯྑ͍ࢦඪͱͳΔɽ঎඼Λ੡଄͢Δձࣾʹͱͬͯɼ঎඼ʹ͍ͭͯɼΞϯέʔτΛऔΒͳͯ͘΋঎඼ͷίϝϯτΛऩूͰ͖Δͱ͍͏ར఺͕͋Δɽͦ͜Ͱɼ‫ײ‬৘ද‫ݱ‬Λ༻͍ͨධ൑෼ੳʹԠ༻͢Δ‫͕ڀݚ‬੝ΜʹߦΘΕ͍ͯΔɽ͔͠͠ɼࠓ·Ͱͷ‫ڀݚ‬ର৅͸୯Ұͷࠃ಺ͷಉ͡‫ޠݴ‬ͷϨϏϡʔσʔλͰ͋Δ͜ͱ͕ଟ͘ɼෳ਺ͷࠃͷؒͰಉ͡঎඼΍αʔϏεʹ͍ͭͯͷධՁͷࠩҟͷ‫ݕ‬ग़΍෼ੳͳͲͷ‫ݚ‬‫ڀ‬͸े෼ʹߦΘΕ͍ͯͳ͍ɽͦ͜Ͱຊ࿦จͰ͸ɼϗςϧͷϨϏϡʔΛରͯ͠ɼੈք֤஍ͷϗςϧʹର͢Δ೔ຊ‫ޠ‬ϨϏϡʔͱதࠃ‫ޠ‬ϨϏϡʔΛର৅σʔλͱͯ͠‫ײ‬৘෼ੳΛ༻͍ͯɼධՁʹ͍ͭͯͷࠩҟͷ‫ݕ‬ग़ɼ෼ੳΛߦ͏ɽΩʔϫʔυ ධ൑෼ੳɼධՁࢹ఺ɼࠩҟ‫ݕ‬ग़ɼ‫ײ‬৘ද‫ݱ‬

Detection of diﬀerences on evaluation points
between Japanese and Chinese
Quan WANG† and Kazutaka SHIMADA††† Graduate School of Computer Science and Systems Engineering†† Department of Artiﬁcial Intelligence
Kyushu Institute of Technology,680-4 Kawazu Iizuka Fukuoka, 820-8502 JapanE-mail: †{q wang,shimada}@pluto.ai.kyutech.ac.jp
Abstract In late years, there are many reviews of products and services on the Web. For general consumers,analyzing these reviews has an important role to select a product or service. For companies, these reviews contain
important information to improve their products or services. Therefore, sentiment analysis for reviews is one ofimportant tasks in natural language processing. However, most of studies for the sentiment analysis have handled
only one nation. In this paper, we focus on diﬀerences on evaluation points between Japanese and Chinese people.
The target is hotel reviews. Our method detects diﬀerences on evaluation points from Japanese and Chinese reviews
about same hotels.
Key words Sentiment analysis, evaluation points, deﬀerence detection, sentiment expressionsධ൑෼ੳΛߦ͏৔߹ɼ·ͣɼධՁ৘ใΛநग़͢Δඞཁ͕͋Δɽ

1. ͸ ͡ Ί ʹධՁ৘ใΛநग़͢Δ୅දతͳख๏ʹɼ‫ײ‬৘ද‫ݱ‬நग़͕‫͛ڍ‬ΒΕɼΠϯλʔωοτͷී‫ʹٴ‬൐͍ɼ WEB ্ʹ͸঎඼΍αʔϏε༷ʑͳ‫ڀݚ‬΍ํ๏࿦͕ఏҊ͞Ε͍ͯΔ [1]ɽ͔͠͠ɼ͜ΕΒͷ‫ݚ‬ʹର͢Δଟ͘ͷධ൑৘ใ͕஝ੵ͞Ε͍ͯΔɽ͜ΕΒͷධ൑Λ෼‫Ͱڀ‬͸ɼଟ͘ͷ৔߹ɼ୯ҰͷࠃΛର৅ͱ͓ͯ͠Γɼෳ਺ͷࠃͷੳ͢Δ͜ͱͰɼϢʔβʔ͕ΠϯλʔωοτγϣοϐϯάΛ͢Δؒͷσʔλʹ͍ͭͯධՁͷ܏޲΍ࠩҟΛ‫ݕ‬ग़͠ɼൺֱ͢Δ‫ڀݚ‬࣌ʹྑ͍ࢦඪͱͳΔɽ·ͨɼ੡඼Λ੡଄͢Δձࣾʹͱͬͯ΋ɼ

͕͋·ΓߦΘΕ͍ͯͳ͍ɽҰํͰɼෳ਺ͷࠃͷؒͷσʔλʹͭ੡඼ʹ͍ͭͯͷίϝϯτΛऩूͰ͖Δͱ͍͏ར఺͕͋Δɽ͜ͷ͍ͯධՁͷࠩҟΛ‫ݕ‬ग़͢Δ͜ͱ͸ධ൑෼ੳͷԠ༻γεςϜͷͨΑ͏ͳ͜ͱ͔Βɼධ൑෼ੳ͸ॏཁͰ͋Δͱߟ͑ΒΕΔɽैདྷͷΊʹେ͖ͳҙٛΛ࣋ͭͱߟ͑ΒΕΔɽྫ͑͹ɼࠃ಺Ͱച্͕ॱ

− 29 −

This article is a technical report without peer review, and its polished and /or extended version may be published elsewhere.
Copyright ©2016—1—by IEICEௐͳ঎඼͕ւ֎ͷࢢ৔Ͱൃച͞Εͯ΋ɼࣗࠃͱಉ༷ʹ͸ചΕͳ

ホテルのレビューサイト

͍৔߹͕͋Δɽ͜Ε͸ࠃʹΑͬͯධՁͷϙΠϯτ͕ҟͳΔͨΊͰ͋Δɽ͕ͨͬͯ͠ɼ੡඼ͷྑ͍ධՁɼѱ͍ධՁΛࠃผͰ෼ੳ

日本語レビュー

͢Δඞཁ͕͋Δɽͦͷ݁ՌΛར༻͢Δ͜ͱͰɼͦΕͧΕͷࠃ΍

このホテル A は立地が良かったࠃຽϚονͨ͠੡඼΍αʔϏεͷվྑ͕ՄೳʹͳΔɽ

中国語レビュー
酒店 A 的床好ຊ‫Ͱڀݚ‬͸ɼϗςϧͷϨϏϡʔΛର৅ͱͨ͠೔தؒͷධՁࠩҟʹண໨͢Δɽࠓճ͸ɼ೔ຊ‫͔ॻͰޠ‬ΕͨϨϏϡʔ͸೔ຊਓ͕機械翻訳機械翻訳ͨ΋ͷͱ͍͏ԾఆΛஔ͖ɼ෼ੳΛ͢Δʢ஫ 1ʣɽࠩҟͷ‫ݕ‬ग़Λ‫ݕ‬ग़

英語（日本語翻訳）

英語（中国語翻訳）

͢Δࡍʹ࠷΋γϯϓϧͳߟ͑ํ͸ɼยํͷ‫ޠݴ‬ͷϨϏϡʔͷΈThe location ofthis hotel A isgood.

ॻ͍ͨ΋ͷͰ͋Γɼதࠃ‫͔ॻͰޠ‬ΕͨϨϏϡʔ͸தࠃਓ͕ॻ͍Ͱ‫ݦ‬ஶʹग़‫͢ݱ‬Δ୯‫ޠ‬Λ୳͠ग़͢͜ͱͰ͋Δɽ͔͠͠ͳ͕ΒɼThe bed of thehotel A is good．

୯७ͳ୯‫ޠ‬ͷස౓͚ͩͰ͸ɼ෼ੳͷର৅ͱ͍ͨ͠ʮධՁͷϙΠϯτʯͷΈΛ෼ੳͰ͖Δͱ͸‫ݶ‬Βͳ͍ɽͦ͜Ͱɼස౓ࠩͷେ͖

単語の頻度差計算および感情語の頻度差計算

͍୯‫܎ͱޠ‬Γड͚ͳͲͷؔ܎ʹ͋Δ‫ײ‬৘ද‫ݱ‬ͷස౓΋෼ੳͷର
৅ͱ͢Δɽ

日本語
location→good・頻度 100
bed→good・頻度 20·ͨɼ෼ੳͷํ๏ͱͯ͠ɼ೔ຊ‫ޠ‬ͷϨϏϡʔΛதࠃ‫ʹޠ‬຋༁ͯ͠෼ੳ͢Δͱ͍͏ख๏΍‫ʹٯ‬தࠃ‫ޠ‬ͷϨϏϡʔΛ೔ຊ‫ʹޠ‬຋༁ͯ͠෼ੳ͢Δͱ͍͏ํ๏ͳͲ͕ߟ͑ΒΕΔ͕ɼ‫ػ‬ց຋༁ͷਫ਼

日本人はホテルの場所を重要視するが中国人はベッドなどの快適さを評価する傾向がありそうだ！

౓͸ 100%Ͱ͸ͳ͍ͨΊɼยํͷ‫ͱ͏·ͯͤ͠دʹޠݴ‬຋༁ͨ͠‫ޠݴ‬ͷΈʹԿΒ͔ͷϊΠζ͕ੜ͡ΔՄೳੑ͕͋Δɽ͞Βʹɼ‫ݱ‬ঢ়Ͱதࠃ‫ޠ‬ͷ‫ײ‬৘෼ੳͷϦιʔε͕๛෋Ͱ͸ͳ͍ͳͲͷ໰୊

ਤ 1 ఏҊख๏ͷ֓ཁɽ΋͋Δɽͦ͜Ͱຊ‫Ͱڀݚ‬͸ɼ྆‫ޠݴ‬Λӳ‫ʹޠ‬຋༁͠ɼ຋༁͞Εͨӳ‫ޠ‬Λ෼ੳ͢Δ͜ͱͰɼ೔தؒͷࠩҟΛ‫ݕ‬ग़͢Δͱ͍͏ΞϓϩʔνΛऔΔɽ
ਤ 1 ʹఏҊख๏ͷ֓ཁΛࣔ͢ɽఏҊख๏Ͱ͸ɼ͍͔ͭ͘ͷ஍Ҭʹଘࡏ͢Δϗςϧʹ͍ͭͯɼͦͷϗςϧʹ͍ͭͯॻ͔Εͨ೔ຊ‫ͱޠ‬தࠃ‫ޠ‬ͷϨϏϡʔΛऩू͢Δɽͦͯ͠ɼͦͷ֤ϨϏϡʔΛ‫ػ‬ց຋༁‫ث‬ʢ஫ 2ʣ Λ༻͍ͯӳ‫ʹޠ‬຋༁͢Δɽ຋༁͞Εͨӳ‫ޠ‬ϨϏϡʔʹରͯ͠ɼස౓ࠩͷ͋Δ୯‫ޠ‬ͷ‫ݕ‬ग़͓Αͼ‫ײ‬৘‫ޠ‬ͷස౓෼ੳΛߦ͍ɼࠩҟީิΛ‫ݕ‬ग़͢Δɽ࣮‫Ͱݧ‬͸ɼ͜ͷಘΒΕͨࠩҟީิͷଥ౰ੑ΍ղऍʹ͍ͭͯਓखͰ෼ੳͨ݁͠ՌΛ‫࡯ߟʹج‬͢Δɽ

中国語
location→good・頻度 5
bed→good・頻度 150಺ͷ߲໨਺ʹ‫ͮ͘ج‬ख๏ɼ(2)Wikipedia ͷ‫಺ࣄه‬ͷࠃ໊ɺ‫ޠݴ‬໊਺ʹ‫ͮ͘ج‬ख๏ɼ(3)Wikipedia ͷ‫͚͓ʹࣄه‬Δࢼචऀͷҙਤʹ‫ͮ͘ج‬ख๏) ͷͲΕΑΓ΋จԽࠩΛ൑ఆ͢Δ࣌ʹߴ͍ਫ਼౓ͱͳΔͱઆ໌͍ͯ͠Δɽ·ͨɼத࡚Β [3] ͷ‫Ͱڀݚ‬͸ɼWikipediaΤϯτϦͷλΠτϧؒͷ‫ؒޠݴ‬ϦϯΫΛ຋༁஌ࣝͱͯ͠༻͍ɼಛʹ೔ӳʹ͓͚Δ Wikipedia ؔ࿈‫ޠ‬Λ༻͍ͨϒϩάαΠτͷ‫ݕ‬ࡧΑΓɼ೔ӳ྆ํͷϒϩάͷؒͷಛఆτϐοΫʹؔͯ͠ɼೋ‫ݴ‬‫ؒޠ‬ͷࠩҟͷ෼ੳख๏ΛఏҊ͍ͯ͠Δɽ෼ੳͨ݁͠Ռͱͯ͠ɼಛʹʮΞϧίʔϧґଘ঱ʯɼʮϦετϥʯɼʮஶ࡞‫ݖ‬৵֐ʯɼʮัܵʯɼʮଁ‫ث‬Ҡ২ʯɼʮ٤ԎʯɼʮαϒϓϥΠϜϩʔϯʯͷ‫ ܭ‬7 τϐο

2. ؔ ࿈ ‫ڀ ݚ‬Ϋʹ͍ͭͯͷ೔ӳؒͰτϐοΫͷؔ৺಺༰͕େ͖͘ҟͳΔ͜ͱ

ຊ‫Ͱڀݚ‬͸ɼதࠃਓͱ೔ຊਓͱͷධՁͷࠩҟΛ‫ݕ‬ग़͢Δ͜ͱΛ໨తʹ͍ͯ͠Δɽ͜ͷࠩҟͱࣅͨΑ͏ͳߟ͑ํͱͯ͠จԽࠩͱ͍͏΋ͷ΋ߟ͑ΒΕΔɽਡ๚Β [2] ͸ɼ೔தؒͷจԽࠩ‫ڀݚ‬ͱͯ͠ɼऩूͨ͠σʔληοτʹରͯ͠ɼWikipedia ͷ೔ຊ‫ޠ‬൛ͱதࠃ‫ޠ‬൛ͷ྆ํʹɼ‫ͯ͠ͱࣄه‬ଘࡏ͢Δ͔Ͱ͋Δ͔Λௐ΂ɼ‫ࣄه‬ͷ಺༰ʹΑΓɼ‫ݩ‬ͷจԽ‫ݍ‬ͷ಺༰Λࢦ͍ͯ͠Δ͕ɼ఻Θ͍ͬͯͨ஌ࣝͷղऍ͕‫׬‬શʹ࠶‫͞ݱ‬Ε͍ͯͳ͍ (͜ΕΛୈ 1 छͷจԽࠩͱ‫͋Ͱ )Ϳݺ‬Δ͔ɼ྆ํͷจԽ‫ʹݍ‬΋ଘࡏ͢Δ͕ɼಉ͡ҙຯͰ͸ͳ͍΋ͷ (ୈ 2 छͷจԽࠩͱ‫͋Ͱ )Ϳݺ‬Δ͔Λ෼ྨ͢Δͱ͍͏จԽࠩ‫ݕ‬ग़ख๏ΛఏҊ͍ͯ͠Δɽͦͷ݁ՌɼఏҊ͞ΕͨจԽࠩ෼ྨख๏͕ैདྷͷࡾͭͷ෼ྨख๏ ((1)Wikipedia ͷ‫ࣄه‬͕෼͔ͬͨɽHu Β [4] ͸தࠃͷϒϩάαΠτ Weibo ͱ೔ຊ‫ޠ‬൛ Twitter ͷؒͰಉ͡τϐοΫ಺༰ʹରͯ͠ɼ೔ຊਓͱதࠃਓͷՁ஋‫؍‬ͷൺֱɼରൺ࣮‫ݧ‬ΛߦͬͨɽՁ஋‫ͯؔ͠ʹ؍‬ɼWeiboϢʔβʔ͸ʮ޷‫ح‬৺ʯͷ࣭Λද͍ͯ͠Δɽ೔ຊͷπΠολʔɾϢʔβʔ͸ʮણࡉʯͷ࣭Λද͍ͯ͠Δͱ͍͏͜ͱ͕෼͔ͬͨɽ
͜ͷΑ͏ʹɼೋࠃؒͷจԽࠩ΍ϒϩά‫ࣄه‬ͷؔ৺ͳͲͷࠩҟʹ͍ͭͯɼൺֱɼ෼ੳ͢Δ‫ڀݚ‬͸ଘࡏ͢Δ͕ɼಉ͡঎඼΍λʔήοτʹରͯ͠ɼೋࠃؒͷϨϏϡʔͷ಺༰ͷൺֱɼ෼ੳ͢Δ‫ݚ‬‫ڀ‬͸ͳ͍ɽຊ‫Ͱڀݚ‬͸ɼϗςϧͷϨϏϡʔʹରͯ͠ɼ೔ຊ‫ޠ‬ϨϏϡʔͱதࠃ‫ޠ‬ϨϏϡʔͷධՁʹ͍ͭͯͷࠩҟͷ‫ݕ‬ग़ɼ෼ੳΛߦ͏ɽ

3. ର৅σʔλʢ஫ 1ʣɿσʔλ਺Λ૿΍ͨ͢Ίʹӳ‫͔ॻͰޠ‬ΕͨϨϏϡʔʹରͯ͠ɼͦͷϨϏϡʔຊ‫Ͱڀݚ‬͸ TripAdvisorʢ஫ 3ʣ ʹ౤ߘ͞Εͨϗςϧʹؔ͢ΔϨʹ෇͍ͨϝλ৘ใʢॻ͖खͷࠃ੶ʣͳͲΛ࢖͏͜ͱ΋ߟ͑ΒΕΔ͕ɼσʔλͷऩूͷ͠΍͢͞΍฼‫͍ͳͰޠ‬ਓ͸ͦͷ‫Ͱޠݴ‬ϨϏϡʔΛॻ͘͜ͱ͸ߟ͑ͮΒ͍͜ͱͳͲ͔Βࠓճ͸͜ͷΑ͏ͳԾఆΛஔ͍ͨɽʢ஫ 2ʣ
ɿMicrosoft Translator: http://www.bing.com/translatorʢ஫ 3ʣɿhttps://www.tripadvisor.jp/− 30 −—2—ϏϡʔΛର৅ͱ͢Δɽ෼ੳର৅͸೔ຊ‫ͱޠ‬தࠃ‫ޠ‬ͷϨϏϡʔͰද 1 ස౓ࠩʹ‫ࠩͮ͘ج‬ҟ‫ݕ‬ग़ͷྫ͋Δ͕ɼͲͷΑ͏ͳϗςϧΛର৅ͱ͢Δ͔ʹΑͬͯ΋ධՁͷϙ୯‫ޠ‬Πϯτ͸ҟͳΔͱߟ͑ΒΕΔɽͦ͜Ͱɼࠓճ͸ͦΕͧΕͷ‫ޠݴ‬

w1ʹΑΔϨϏϡʔͷଟ͍தࠃɼ೔ຊɼͦͯ͠ΞϝϦΧʹ͋ΔϗςϧͷϨϏϡʔΛର৅ͱ͢Δɽ·ͨɼ೔ຊͷϗςϧ΍தࠃͷϗς೔ຊ‫ޠ‬ͷස౓ தࠃ‫ޠ‬ͷස౓

10010

w25090w310001200ϧͱ͍ͬͨ޿͍ൣғ͔Β୯ʹ౤ߘ਺ͷଟ͍ϨϏϡʔΛऩू͢Δ
ද 1 Λ༻͍ͯઆ໌͢Δɽ͜ͷදͷ৔߹ɼ୯‫ ޠ‬w1 ͷ೔ຊ‫ޠ‬ͷͱద੾ͳ೔தؒͷࠩҟΛ‫ݕ‬ग़Ͱ͖ͳ͍Մೳੑ͕͋Δɽྫ͑͹ɼ෼ੳର৅ͱͳΔΞϝϦΧͷ͋Δϗςϧ͕ւʹ໘ͨ͠ϦκʔτϨϏϡʔͰͷग़‫ݱ‬ස౓ (100) ͱதࠃ‫Ͱޠ‬ͷग़‫ݱ‬ස౓ (10) ʹ͸஍ʹଘࡏ͠ɼւʹ໘ͨ͠Ϧκʔτ஍ͷϗςϧ͸શମͷϗςϧͷ

1.5 ഒҎ্ͷ͕ࠩ͋Δɽಉ༷ʹɼw2 ͸தࠃ‫( ޠ‬90) ͱ೔ຊ‫( ޠ‬50)ߴʑ਺ύʔηϯτ͔͠ͳ͍৔߹Λ૝૾ͯ͠ཉ͍͠ɽ͜͜Ͱɼ೔

ʹ 1.5 ഒҎ্ͷ͕ࠩ͋Δɽ͕ͨͬͯ͠ɼఏҊख๏Ͱ͸ w1 Λ೔ຊ‫ͱޠ‬ൺֱ͢Δͱɼதࠃ‫ޠ‬ͷϨϏϡʔʹʮւ͕៉ྷʯ΍ʮ៉ྷຊਓ͕ධՁ͢Δ܏޲ͷ͋Δ‫ޠ‬ʢࠩҟ୯‫ޠ‬ʣͱ͠ɼw2 Λதࠃਓ͕ͳ࠭඿ʯͳͲͷද‫͕ݱ‬ग़‫ͱͨ͠ݱ‬Ծఆ͠Α͏ɽσʔλͷઈର਺

ධՁ͢Δ܏޲ͷ͋Δ‫ޠ‬ʢಉࠩ͘͡ҟ୯‫ޠ‬ʣͱͯ͠ѻ͏ɽw3 ͸͕ଟ͚Ε͹͜ͷதࠃ‫ͱޠ‬೔ຊ‫Ͱޠ‬ͷग़‫ݱ‬ස౓ࠩʹ͸೔தؒͷࠩߴස౓‫Ͱޠ‬͸͋Δ͕ɼ͓‫͍ޓ‬ͷ‫Ͱޠݴ‬ͷग़‫ʹ਺ݱ‬ᮢ஋ n Ҏ্ͷҟͱͯ͠ҙຯ͕͋Δ͔΋͠Εͳ͍ɽ͔͠͠ɼͦͷΑ͏ͳϗςϧ͕ࠩͳ͍ͨΊɼࠩҟͷͳ͍୯‫ͯ͠ͱޠ‬Ҏ߱ͷॲཧͰ͸ର৅֎ͱ͕গ਺Ͱ͋Ε͹ɼͦΕ͕೔தؒͷධՁͷࠩҟͳͷ͔ɼ୯ͳΔϗ͢Δɽςϧͷཱ஍ʹӨ‫ൃۮͨ͠ڹ‬తͳස౓ࠩͳͷ͔ͷ൑அ͕೉͘͠ͳ

4. 2 ‫ײ‬৘ද‫ࠩͮ͘جʹݱ‬ҟͷ‫ݕ‬ग़Δɽ͜ͷΑ͏ͳ໰୊Λආ͚ΔͨΊʹɼ֤஍ҬͰͷϗςϧͷબఆલઅͰ͸ɼස౓ࠩʹ‫ͮ͘ج‬୯७ͳࠩҟ‫ݕ‬ग़ͷख๏Λઆ໌ͨ͠ɽʹ͸ɼपล‫Ͳͳڥ؀‬ͷ৚͕݅ಉ͡ʹͳΔΑ͏ʹ͢Δඞཁ͕͋Δɽ͔͠͠ɼ୯ͳΔස౓ͷࠩΛ‫ݟ‬Δ͚ͩͰ͸ɼ͋Δ୯‫ʹޠ‬ରͯ͠ɼຊ࿦จͰ͸ɼ۩ମతʹ͸ɼϗςϧͷ৔ॴ͸౎ࢢ෦Ͱɼۙ͘ʹӺͲ͏ධՁ͍ͯ͠Δͷ͔͕൑அͰ͖ͳ͍ɽ‫͑׵͍ݴ‬Δͱɼ೔ຊਓ΍஍Լమ͕͋ΔɼΞΫηε͕ྑ͍৔ॴͱͨ͠ɽͱதࠃਓͷධՁ܏޲ͷࠩҟ·Ͱ͸൑அͰ͖ͳ͍ɽྫ͑͹ɼʮ‫ݐ‬͞ΒʹɼϗςϧͷάϨʔυʹΑͬͯ΋ධՁͷϙΠϯτ͸ҟͳ෺ʯͱ͍͏୯‫͕ޠ‬ɼ೔தؒͰස౓͕ࠩ͋ͬͨͱ͠Α͏ɽ͜ͷ‫ݕ‬Δͱߟ͑ΒΕΔɽྫ͑͹ɼߴ‫ڃ‬ϗςϧͱϏδωεϗςϧͰ͸ɼग़͞Εͨࠩҟʹҙຯ͕ͳ͍Θ͚Ͱ͸ͳ͍͕ɼ͜Ε͚ͩͰ͸े෼ධՁͷϙΠϯτ͕ҟͳΔͰ͋Ζ͏ɽ͕ͨͬͯ͠ɼຊ࿦จͰ͸͜Ͱ͸ͳ͍ɽ͞Βʹղੳ͠ɼྫ͑͹ʮ‫ݐ‬෺͕៉ྷʯͷΑ͏ͳද‫ݱ‬

ͷ 2 छྨΛ෼͚ͯऩू͢Δɽ͕நग़͞ΕΕ͹ɼࠩҟʹؔ͢Δཧղ͕ਂ·Δɽࠓճ͸தࠃɼ೔ຊɼΞϝϦΧʹ͋Δߴ‫ڃ‬ϗςϧͦΕͧΕʹର͜ͷΑ͏ͳ໰୊Λղফ͢ΔͨΊʹɼຊ࿦จͰ͸‫ײ‬৘ද‫ʹݱ‬ணͯ͠೔ຊ‫ޠ‬ϨϏϡʔ 3000 ݅ɼதࠃ‫ޠ‬ϨϏϡʔ 3000 ݅Λऩू͠

໨͢Δɽ‫ײ‬৘ද‫ͱݱ‬͸ɼςΩετதͷॻ͖खͷओ‫؍‬తͳද‫Ͱݱ‬ͨɽಉ༷ʹɼ֤஍ҬͷϏδωεϗςϧʹରͯ͠೔ຊ‫ޠ‬ϨϏϡʔ͋Δɽ͜Εʹ͸ྑ͍ɼѱ͍ͱ͍ͬͨ‫ܗ‬༰ࢺʹ‫ݶ‬Βͣɼຬ଍͢Δɼ

3000 ݅ɼதࠃ‫ޠ‬ϨϏϡʔ 3000 ݅Λऩूͨ͠ɽͦͷ݁Ռɼߴ‫ڃ‬མ୾ͤ͞Δͱ͍ͬͨಈࢺ΍ɼઈ඼ɼܽؕͱ໊͍ͬͨࢺ΋‫·ؚ‬Εϗςϧͷσʔλ਺͸ 18000 ݅ɼϏδωεϗςϧͷσʔλ਺͸Δɽຊ࿦จͰ͸ɼ‫ײ‬৘ද‫ ͯ͠ͱॻࣙݱ‬SentiWordNetʢ஫ 5ʣ Λར

18000 ݅ͱͳΓɼҎ߱͸͜ͷ 2 ͭͷσʔληοτΛ෼ੳͷର৅

༻͢Δɽ‫ײ‬৘ද‫ॻࣙݱ‬Λར༻͢Δ͜ͱͰɼ্‫ه‬ͷʮ‫ݐ‬෺͕៉ྷʯ

ͱ͢Δɽ

ͷΑ͏ͳධՁͷϙΠϯτΛநग़Ͱ͖Δ͚ͩͰ͸ͳ͘ɼʮ‫ݐ‬෺ʹண͍ͨʯͷΑ͏ͳධՁͷࠩҟ‫ݕ‬ग़ʹ͸ແؔ܎ͳཁૉΛநग़͠ͳ͘

4. ධՁͷࠩҟ‫ݕ‬ग़ͳΔͱ͍͏ϝϦοτ΋͋Δɽຊ࿦จͰ͸ɼ‫ײ‬৘ද‫ݱ‬Λߟྀͨ͠είΞͰ͋Δ‫ײ‬৘ද‫ݱ‬ൺ཰ຊઅͰ͸ 3. અͰड़΂ͨσʔληοτ͔Β೔தؒͷࠩҟΛ‫ݕ‬ग़͢Δख๏ʹ͍ͭͯड़΂ΔɽఏҊख๏Ͱ͸ɼ·ͣɼ೔ຊ‫ޠ‬Ϩ(sr) Λ‫͠ࢉܭ‬ɼධՁͷࠩҟͷ‫ݕ‬ग़ʹར༻͢Δɽ·ͣɼස౓ࠩʹϏϡʔͱதࠃ‫ޠ‬ϨϏϡʔΛ‫ػ‬ց຋༁Λ࢖ͬͯ຋༁͠ɼಉ͡‫ޠݴ‬Αͬͯ‫ݕ‬ग़͞Εͨࠩҟͷ͋Δ୯‫ޠ‬ͷ܎Γઌͱ܎Γ‫ݩ‬ͷ‫ײ‬৘ද‫ݱ‬ʢӳ‫ޠ‬ʣʹ·ͱΊΔɽ࣍͸ӳ‫ޠ‬ͷࣗવ‫ޠݴ‬πʔϧͰ͋Δ StanfordΛ‫ײ‬৘ද‫ॻࣙݱ‬Λ༻͍ͯಛఆ͢Δɽͦͷ݁ՌΛ༻͍ͯɼsr ͸ҎCoreNLPʢ஫ 4ʣ Λ༻͍ͯɼ຋༁ͨ͠ϨϏϡʔΛղੳ͢ΔɽࠩҟԼͷࣜͰ‫͞ࢉܭ‬ΕΔɽ‫ݕ‬ग़Ͱ͸ɼ·ͣɼग़‫ݱ‬ස౓ࠩʹ‫͘ૈ͖ͮج‬೔தؒͷࠩҟΛ‫ݕ‬ग़sr(wi ) =͢Δɽͦͷ‫ޙ‬ɼ‫ײ‬৘‫ޠ‬Λར༻ͯ͠ΑΓৄࡉͳධՁͷࠩҟΛ෼ੳ͢Δɽ

sentiN um(wi )f req(wi )͜ ͜ Ͱ wi ͸ ස ౓ ࠩ ʹ ‫ ݕ ͖ ͮ ج‬ग़ ͞ Ε ͨ ࠩ ҟ ୯ ‫ ͋ Ͱ ޠ‬Δ ɽ4. 1 ස౓ࠩʹ‫ࠩͮ͘ج‬ҟͷ‫ݕ‬ग़

f req(wi ) ͸ wi ͷස౓Ͱ͋Γɼද 1 ͷ w1 Ͱ͋Ε͹ 100ɼw2࠷΋୯७ͳҧ͍Λ‫ݕ‬ग़͢Δํ๏͸೔தͷϨϏϡʔؒͰͷ୯‫ޠ‬Ͱ͋Ε͹ 90 ʹ૬౰͢ΔɽsentiN um(wi ) ͸ wi ͱ܎Γड͚ؔස౓ͷࠩʹண໨͢Δ͜ͱͰ͋Δɽ͢ͳΘͪɼ͋Δ୯‫ޠ‬ͷ೔ຊ‫ޠ‬܎ͷ͋Δ‫ײ‬৘ද‫ݱ‬ͷ਺Λද͢ɽྫ͑͹ɼw1 ͱ܎͍ͬͯΔ goodͰͷग़‫ݱ‬ස౓ͱதࠃ‫Ͱޠ‬ͷग़‫ݱ‬ස౓ʹ n ഒҎ্ͷ͕ࠩ͋Ε͹ɼ

͕ 20 ճɼnice ͕ 10 ճɼexcellent ͕ 30 ճग़‫͍ͯ͠ݱ‬Ε͹ɼͦΕ͸೔தؒͰධՁʹࠩҟ͕͋ΔͱΈͳ͢ɽ͜ͷख๏Ͱ͸ɼnsentiN um(wi ) = 60 Ͱ͋Γɼsr(w1 ) = 0.6 ͱͳΔɽ͜ͷ஋͕ΛͲͷΑ͏ͳ஋ͱ͢Δ͔ʹΑͬͯ݁Ռ͕ҟͳΔ͕ɼࠓճ͸‫ݧܦ‬ߴ͍΄Ͳ܎Γड͚ؔ܎ͷ͋Δ‫ײ‬৘ද‫͕ݱ‬ଟ͘ଘࡏ͢Δ͜ͱΛҙతʹ n = 1.5 ͱ͢Δɽຯ͢ΔͨΊɼධՁͷࠩҟͱͯ͠༗๬ͳ୯‫͋Ͱޠ‬Δ͜ͱΛҙຯ͠

ʢ஫ 4ʣ
ɿhttp://stanfordnlp.github.io/CoreNLP/ʢ஫ 5ʣɿhttp://sentiwordnet.isti.cnr.it/− 31 −—3—ද2஍ҬͷมԽͷӨ‫ڹ‬Λड͚͍ͯͳ͍୯‫ޠ‬ʢߴ‫ڃ‬ϗςϧʣΞϝϦΧ୯‫ޠ‬೔ຊ‫ޠ‬ͷස౓தࠃ೔ຊதࠃ‫ޠ‬ͷස౓ ೔ຊ‫ޠ‬ͷස౓ தࠃ‫ޠ‬ͷස౓ ೔ຊ‫ޠ‬ͷස౓3 ஍Ҭ౷߹தࠃ‫ޠ‬ͷස౓ ೔ຊ‫ޠ‬ͷස౓ தࠃ‫ޠ‬ͷස౓

station

823

189

1016

340

2025

1424

3864

1953

check-in

676

361

243

148

302

166

1221

675

check-out

186

125

155

119

172

91

513

335

breakfast

618

362

1557

1035

1246

753

3421

2150

coﬀee

317

144

256

68

185

43

758

255

bed

602916

354

563

297

507

1253

1986

bathroom

358

572

274

454

323

618

955

1644

decoration

19

152

18

448

13

118

50

718

swimming-pool

30

91

110

153

37

74

177

318

bar

76

196

178

228

87

155

341

579

͍ͯΔɽ͜ͷ৔߹΋ɼ೔தؒͰ n ഒҎ্ͷ͕ࠩ͋Δ৔߹ΛࠩҟͲʣ͸தࠃਓ͕ධՁ͢ΔϙΠϯτͱͯ͠‫ݕ‬ग़͞Εͨ͜ͱΛҙຯ͕͋Δͱ‫Ϳݺ‬ɽn ͷ஋͸ස౓ͷͱ͖ͱಉ༷ʹ 1.5 Ͱ͋Δɽ͢Δɽ

sr Λ༻͍Δ͜ͱͰ‫ײ‬৘ද‫ݱ‬ͷ͋Δࠩҟ୯‫ޠ‬Λ‫ݕ‬ग़͢Δ͜ͱ͕͜ͷ݁Ռʹ͍ͭͯɼ͞Βʹ‫ײ‬৘ද‫ͮ͘جʹݱ‬ख๏ (4. 2 અ) ΛՄೳʹͳΔ͕ɼͦͷ··Ͱ͸ɼͦͷࠩҟͷ͋Δ୯‫ߠ͕ޠ‬ఆతͳద༻͠ɼΑΓਂ͘ධՁͷࠩҟʹ͍ͭͯߟ࡯͢Δɽද 3 ͸ද 2 ͷධՁΛҙຯ͢Δͷ͔൱ఆతͳධՁΛҙຯ͢Δͷ͔͸൑அͰ͖ͳ୯‫܎ͱޠ‬Γड͚ؔ܎ͷ͋Δ‫ײ‬৘ද‫ͦͱݱ‬ͷස౓Λද͍ͯ͠Δɽ͍ɽͦ͜ͰɼҎԼͷࣜͰ wi ͷߠఆ౓ fp (wi ) ͱ൱ఆ౓ fn (wi )‫ײ‬৘ද‫ݱ‬ͷྡʹ͋Δ‫಺ހׅ‬ͷ਺ࣈ͸ͦͷ‫ײ‬৘ද‫͕ݱ‬ස౓ࠩʹΛࢉग़͢ΔɽΑΔࠩҟ୯‫܎ͱޠ‬Γड͚ؔ܎ͷ͋Δ‫ײ‬৘ද‫ݱ͕ݱ‬Εͨ਺Ͱ͋fp (wi ) =fn (wi ) =Δɽ͢ͳΘͪɼ೔ຊ‫ Ͱޠ‬3864 ճग़‫ͨ͠ݱ‬୯‫ ޠ‬station ͱ܎Γn∑1
posW ordj
sentN um(wi ) j=1

ड͚ؔ܎ͷ͋Δ good ͕ 60 ճɼgreat ͕ 25 ճɼexcellent ͕ 3ճग़‫ͱͨ͜͠ݱ‬Λҙຯ͍ͯ͠Δɽ͜ͷද͔Βස౓ࠩͷେ͖͍୯n∑‫Ͳ͕ޠ‬ͷΑ͏ͳ఺ʹ͍ͭͯධՁ͞Ε͍ͯΔ͔ΛཧղͰ͖Δɽྫ

1
negW ordj
sentN um(wi ) j=1

͑͹ɼcheck-in Ͱ͸ɼ೔ຊ‫Ͱޠ‬΋தࠃ‫Ͱޠ‬΋ good ΍ smoothɼ͜͜Ͱ posW ordj ͸ࠩҟͷ͋Δ୯‫( ޠ‬wi ) ͷͱ܎Γड͚ؔ܎ͷ͋Δ‫ײ‬৘ද‫ݱ‬ͷ͏ͪɼߠఆతͳҙຯΛ࣋ͭ୯‫ޠ‬Λද͠ɼnegW ordj͸൱ఆతͳҙຯΛ࣋ͭ୯‫ޠ‬Λද͢ɽ͜ͷ਺஋Λൺֱ͢Δ͜ͱͰwi ͕ߠఆతͳධՁϙΠϯτʹؔ͢Δࠩҟͳͷ͔൱ఆతͳධՁϙΠϯτʹؔ͢Δࠩҟͳͷ͔Λ༰қʹ೺ѲͰ͖Δɽ

quickly ͳͲͷ‫ײ‬৘ද‫͓ͯ͠ىڞ͕ݱ‬ΓɼʮνΣοΫΠϯ͕εϜʔζͩͬͨʯͱ͍͏Α͏ͳྑ͍ධՁΛ͍ͯ͠Δ͜ͱ͕෼͔ΔɽҰํͰɼධՁͷ܏޲͸ಉ͕ͩ͡ɼcheck-in ͷग़‫ݱ‬ස౓ͷࠩʢ1221
ͱ 675ʣ͔Βɼ೔ຊਓ͕͜ͷΑ͏ͳνΣοΫΠϯͷշద͞ΛதࠃਓΑΓ΋ॏཁͳධՁϙΠϯτͩͱ‫͍ͯ͡ײ‬Δͱ͍͏ղऍ͕Ͱ
͖Δɽcoﬀee ʹ͍ͭͯ͸ɼ೔ຊ‫ޠ‬ͷΈ plenty ͷΑ͏ͳྔΛද

5. ࣮‫ݧ‬ɾߟ࡯͢‫ײ‬৘ද‫͕ݱ‬ଘࡏ͍ͯ͠Δɽ͜Ε͔Β೔ຊਓ͕ఏ‫͞ڙ‬Εͨίʔ

3. અͰऩूͨ͠ϨϏϡʔσʔλʹରͯ͠ɼఏҊख๏ʹ‫͖ͮج‬ɼࠩҟΛ‫ݕ‬ग़͢ΔɽఏҊख๏Λద༻ͨ͠ͱ͜Ζɼ஍ҬʢΞϝϦΧɼ೔ຊɼதࠃʣʹΑͬͯ܏޲͕มΘΒͳ͍୯‫ͱޠ‬஍ҬʹΑͬͯ܏޲͕มΘΔ୯‫͕ޠ‬ଘࡏͨ͠ɽ஍ҬʹΑͬͯ܏޲͕มΘΒͳ͍୯‫ޠ‬͸ຊ࿦จͰఆٛͨࠩ͠ҟͰ͋Δͱߟ͑ΒΕΔɽ͜Εʹ͍ͭͯ
͸ 5. 1 અͰߴ‫ڃ‬ϗςϧͱϏδωεϗςϧΛ۠ผͳ͕Βઆ໌͍ͯ͘͠ɽҰํͰɼ஍ҬʹΑͬͯ܏޲͕มΘΔ୯‫ޠ‬͸೔தؒͷධՁͷࠩҟͰ͸ͳ͘ɼಛผͳ‫ݪ‬Ҽ͕͋Δͱߟ͑ΒΕΔɽ͜Εʹ͍ͭͯ͸ 5. 2 અͰࣄྫʹ‫͢࡯ߟ͖ͮج‬Δɽώʔͷྔ΍छྨͳͲͷ๛෋͞ΛධՁ͢Δ͜ͱ͕Θ͔Δɽ࣍ʹ‫ײ‬৘ද‫ݱ‬ൺ཰ sr ͱߠఆ౓ fp ʹ͍ͭͯ‫ͯݟ‬ΈΔʢ஫ 7ʣɽද

4 ʹද 2 ͷ୯‫ؔ͢ʹޠ‬ΔͦΕͧΕͷ஋Λࣔ͢ɽදதͷଠࣈ͸೔ຊ‫ͱޠ‬தࠃ‫ Ͱޠ‬1.5 ഒҎ্ͷ͕ࠩ͋Δ΋ͷͰ͋Δɽදͷ srείΞ͔Βɼ೔ຊਓͷ‫ײ‬৘ද‫ݱ‬Λ౿·͑ͨதࠃਓͱͷࠩҟ͸

stationɼcheck-inɼcoﬀee ͳͲͰ͋Δ͜ͱ͕Θ͔ΔɽҰํͰɼதࠃਓ͕೔ຊਓΑΓ΋‫͢ʹؾ‬ΔϙΠϯτ͸ bed ΍ bathroomɼbarͳͲͰ͋Δ͜ͱ͕Θ͔Δɽ·ͨɼ೔ຊ‫͍͓ͯʹޠ‬͸ check-in ΍check-out ͕ߠఆతධՁΛɼதࠃ‫͍͓ͯʹޠ‬͸ bar ͕ߠఆతධՁΛड͚͍ͯΔ͜ͱ΋Θ͔Δɽ͜ͷ݁ՌΛ·ͱΊΔͱɼ೔ຊਓ

5. 1 ஍ҬʹΑͬͯ܏޲͕มΘΒͳ͍୯‫ޠ‬·ͣɼ୯७ͳස౓ࠩʹ‫ͮ͘ج‬ख๏ (4. 1 અ) ͷ݁Ռʹ͍ͭͯઆ
໌͢Δɽද 2 ʹߴ‫ڃ‬ϗςϧʹؔͯ͠஍Ҭ͝ͱͷ೔ຊ‫͓ޠ‬Αͼதࠃ‫Ͱޠ‬ͷग़‫ݱ‬ස౓ͱ 3 ͭͷ஍ҬΛ౷߹ͨ͠৔߹ͷ݁ՌΛࣔ͢ɽදதͷଠࣈ͸೔தؒͰස౓͕ଟ͍ํΛҙຯ͍ͯ͠Δʢ஫ 6ʣɽ͢ͳΘͪɼදͷ্ଆͷ୯‫ޠ‬ʢstation ΍ breakfastɼcoﬀee ͳͲʣ͸͸ϗςϧͷཱ஍৚݅ʢstationʣ΍αʔϏεʢcheck-in ΍ coﬀeeʣΛධՁ͢Δ܏޲͕͋Δͷʹର͠ɼதࠃਓ͸ϗςϧͷࢪઃ໘Λධ
Ձ͢Δ܏޲͕͋Δ͜ͱ͕Θ͔Δɽ
ҰํͰɼதࠃਓ͕ධՁ͢Δ܏޲ʹ͋Δࢪઃʹؔ͢Δ߲໨Ͱ

decoration ͷ sr είΞʹ͍ͭͯ͸೔ຊ‫ޠ‬ͷํ͕ߴ͘ͳͬͨɽ͜

೔ຊਓ͕ධՁ͢ΔϙΠϯτͰ͋ΓɼԼଆʢbed ΍ decoration ͳʢ஫ 7ʣɿ൱ఆ౓ fn ʹؔͯ͠͸໌֬ͳࠩͷ͋Δ୯‫͕ޠ‬ଘࡏ͠ͳ͔ͬͨͨΊলུ͢
ʢ஫ 6ʣ
ɿ౰વ 1.5 ഒҎ্ͷࠩͷ͋ΔཁૉͰ͋Δɽ

Δɽ

− 32 −—4—ද3୯‫ޠ‬೔ຊ‫ޠ‬ͷස౓

station3864

check-in1221

check-out513breakfast

3421

coﬀee758ߴ‫ڃ‬ϗςϧʹؔ͢Δස౓ࠩͷେ͖͍‫ͦͱޠ‬Εͱ‫͢ىڞ‬Δ‫ײ‬৘ද‫ݱ‬ɽ‫ײ‬৘ද‫ͦͱݱ‬ͷස౓ தࠃ‫ޠ‬ͷස౓
good (60), great (25), excellent (3),close (179), nearest (147), helpful (14),usefu (32), convenien (269)1953
good(64),great(6),smooth(88),quickly(24),early(16),eﬃcient(39),helpful(4),comfortable(40)ɹ675perfect(5), nice(17), smooth(32),early(9), available(26), helpful(2),comfortably(31)335
good(73), nice(15), great(48),excellent(46), perfect(4), available(15),provided(7), free(70), delicious(123),
variety(43), plentiful(13),satisﬁed(30), enjoyed(3)2150
excellent(33), good(13),free(47), provided(5), available(3),delicious(46), plenty(24)
255

1253

good(31), excellent(4), nice(6),big(5), large(23), spacious(41),
comfortable(92), ﬂuﬀy(9), clean(23)1986bathroom955

good(7), nice(17), excellent(9),large(20), spacious(35), huge(3),relaxed(2), comfortable(11),clean(48), luxury(8)1644decoration50

good(1), nice(5), beautiful(5),impressive(1), luxurious(2)718swimming-pool177

nice(6), wonderful(7), enjoyed(6)

318

bar

341

nice(11), good(2), excellent(1), wonderful(6),available(5), enjoyed(12), relaxing(14)

579

bed

good (5), excellent (2), close (52),nearest (10), convenient (69)great(5),quickly(31),early(17)simple(9),fast(12),smooth(7),eﬃcient(10)nice(2), excellent(1), perfect(3)early(16), fast(5) quickly(23)smooth(2), complimentary(9)good(60), great(33), excellent(30),nice(19), wonderful(5), provides(6),available(3), free(23),delicious(43), variety(5), rich(9),satisﬁed(2)good(6), great(3), wonderful(1),supply(1), free(16), available(8),delicious(3), aromatic(2)good(27), excellent(22), great(16),nice(10), large(97), big(11),huge(11), spacious(15),soft(7), comfortable(417)
good(46), nice(45), great(25),excellent(9), large(84), spacious(66),big(33), huge(22),comfortable(9), clean(50),luxury(34)good(30), great(4), nice(6),beautiful(7), modern(5), fashion(2),luxurious(15)nice(14), great(8), good(11),amazing(7), beautiful(13), large(15)good(24), great(39), wonderful(14),nice(6), enjoyed(30), beautiful(10),interesting(16)ϗςϧʹؔ͢Δස౓ࠩͷ܏޲͸ߴ‫ڃ‬ϗςϧͷ΋ͷͱେ͖͘มΘද 4 ߴ‫ڃ‬ϗςϧʹؔ͢Δ‫ײ‬৘ද‫ݱ‬ൺ཰ sr ͱߠఆ౓ fp୯‫ޠ‬‫ײ‬৘ද‫ͦͱݱ‬ͷස౓೔ຊ‫ ޠ‬srதࠃ‫ ޠ‬sr೔ຊ‫ ޠ‬fpதࠃ‫ ޠ‬fpΒͳ͔ͬͨͨΊɼද 2 ʹ૬౰͢ΔϏδωεϗςϧʹؔ͢Δू‫ܭ‬

station

0.189

0.071

0.452

0.430

݁Ռ͸লུ͢ΔɽҰํͰɼ‫ײ‬৘ද‫ͱݱ‬ͷؔ܎͸ߴ‫ڃ‬ϗςϧͷ৔check-in

0.230

0.135

0.517

0.223

check-out

0.238

0.182

0.548

0.200

߹ͱҟͳΔ෦෼͕ଘࡏͨ͠ɽද 5 ʹͦͷ݁ՌΛࣔ͢ɽߴ‫ڃ‬ϗς

breakfast

0.143

0.111

0.577

0.659

coﬀee

0.226

0.157

0.551

0.481

bed

0.187

0.319

0.439

0.527

bed ΍ bathroom ͷ small ΍ noise ͷ terrible ͳͲͰ͋Δɽ͜

bathroom

0.168

0.257

0.413

0.401

ͷ݁ՌΛ౿·͑ͯɼϏδωεϗςϧʹର͢Δ sr ͱ൱ఆ౓ fn Λdecoration

0.280

0.096

0.737

0.688

ࢉग़͢Δɽද 6 ʹͦͷ݁ՌΛࣔ͢ɽද͔Β bed ͱ bathroom ʹswimming-pool

0.107

0.214

0.670

0.673

͍ͭͯதࠃਓͷํ͕‫͍ڧ‬൓ԠΛࣔ͠ɼͦͷ fn ͷ஋͔ΒͦΕ͕

bar

0.150

0.24

0.446

0.645

ϧͷ৔߹ɼଘࡏ͢Δ‫ײ‬৘ද‫ݱ‬͸ߠఆతͳ΋ͷ͕ଟ͔͕ͬͨɼϏδωεϗςϧͷ৔߹͸൱ఆతͳධՁ͕ଟ͘ΈΒΕͨɽྫ͑͹൱ఆతͰ͋Δ͜ͱ͕Θ͔Δɽಉ༷ʹ noise ʹ͍ͭͯ͸೔ຊਓ͕‫͘ڧ‬൱ఆతʹ൓Ԡ͍ͯ͠Δ͜ͱ΋‫ͯݟ‬औΕΔɽධՁ͕൱ఆతͳ

Ε͸௚‫ײ‬΍ଞͷ෼ੳ݁Ռͱ͸ҟͳΔ݁ՌͰ͋Δɽ͔͠͠ɼස౓

ଆ໘ʹ͸ͳ͍ͬͯΔ͕ɼதࠃਓ͕ࢪઃʢbed ͱ bathroomʣʹͷ఺ʢද 3ʣͰ‫ݟ‬Δͱ decoration ͸தࠃ‫ޠ‬ͷϨϏϡʔ͕೔ຊ‫ޠ‬ධՁͷϙΠϯτΛஔ͍͍ͯΔ఺͸มΘΒͣɼ͜Ε͸೔தؒͷධͱൺ΂ͯѹ౗తʹଟ͍ʢ718 ͱ 50ʣɽ͜Ε͸ sr είΞͷࢉग़Ձͷࠩҟͱ͍͑ΔͩΖ͏ɽnoise ͸ߴ‫ڃ‬ϗςϧͰ͸ग़‫͍ͯ͠ݱ‬ํ๏ʹ໰୊͕͋ͬͨͱߟ͑ΒΕΔɽsr είΞ͸ࠩҟ୯‫ޠ‬ͷग़‫ݱ‬ͳ͍ࠩҟ୯‫͋Ͱޠ‬Δ͕ɼ͜Ε͸ϗςϧͷཱ஍తͳ‫Ͳͳڥ؀‬Λදස౓ʹର͢Δ‫ײ‬৘ද‫ݱ‬ͷ୯ͳΔൺ཰Ͱ͋Γɼࠩҟ୯‫ޠ‬ʢ͜ͷ৔͍ͯ͠Δͱߟ͑ΒΕɼߴ‫ڃ‬ϗςϧͰཱ஍໘ʢӺͱͷۙ͞ͳͲʣ

߹͸ decorationʣͷස౓Λແࢹͨ͠‫͍ͯͬͳʹࣜࢉܭ‬ΔɽͦͷΛධՁ͍ͯͨ͠೔ຊਓͷධՁͷϙΠϯτͱҰக͍ͯ͠ΔɽҎ্͔Βɼߴ‫ڃ‬ϗςϧͰ͸ߠఆతͳ໘͕ϨϏϡʔʹ‫ݱ‬Ε΍݁͢ՌɼࠓճͷΑ͏ͳ௚‫ͱײ‬ͷ‫ٯ‬స͕ੜ͍ͯ͡ΔɽΑΓద੾ͳ sr͍͜ͱɼϏδωεϗςϧͰ͸൱ఆతͳଆ໘͕‫ݱ‬Ε΍͍͢͜ͱͳείΞͷࢉग़ํ๏ͷߟ࡯͸ࠓ‫ޙ‬ͷ՝୊Ͱ͋Δɽ࣍ʹϏδωεϗςϧʹ࣮ؔͯ͠‫݁ݧ‬ՌΛߟ࡯͢ΔɽϏδωεͲͷ܏޲ͷࠩ͸͋Δ͕ɼ྆ํͷσʔλͰҰ؏ͯ͠೔ຊਓ͕ධՁ

− 33 −—5—ද 5 Ϗδωεϗςϧʹؔ͢Δස౓ࠩͷେ͖͍‫ͦͱޠ‬Εͱ‫͢ىڞ‬Δ‫ײ‬৘ද‫ݱ‬ɽ୯‫ޠ‬೔ຊ‫ޠ‬ͷස౓‫ײ‬৘ද‫ͦͱݱ‬ͷස౓தࠃ‫ޠ‬ͷස౓

bed

1521

small(30), narrow(21), dislike(5),2451

bathroom721

small(39), narrow(15), dirty(5)noise

462 terrible(52), dislike(9), unwanted(32), annoyed(1)‫ײ‬৘ද‫ͦͱݱ‬ͷස౓small(131), narrow(30), short(7),hard(15),uncomfortable(96)1650 small(249), narrow(6), old(12), bad(1)157

bad(6), terrible(13)͢ΔϙΠϯτͱதࠃਓ͕ධՁ͢ΔϙΠϯτͷࠩҟ͕ಘΒΕ͍ͯ

ද 6 Ϗδωεϗςϧʹؔ͢Δ‫ײ‬৘ද‫ݱ‬ൺ཰ sr ͱ൱ఆ౓ fnΔɽ͜ͷΑ͏ͳࠩҟ͕Θ͔Ε͹ɼྫ͑͹೔ຊਓ٬Λड͚ೖΕΔ୯‫ޠ‬೔ຊ‫ ޠ‬srதࠃ‫ ޠ‬sr೔ຊ‫ ޠ‬fnதࠃ‫ ޠ‬fnͱ͖ʹͲͷΑ͏ͳ఺ʹྗΛೖΕΕ͹ߴ͍ධՁΛ΋Β͑Δ͔ɼ‫ٯ‬

bed0.037

0.114-0.350-0.493ʹதࠃਓͷ৔߹ʹ͸Ͳ͜ʹྗΛೖΕΕ͹ྑ͍͔͕Θ͔Γɼϗςbathroom

0.082

0.162

-0.374-0.374

noise

0.203

0.121

-0.546-0.669ϧ͕ద੾Ͱޮ཰ͷྑ͍٬ͷड͚ೖΕઓུΛ࿅Δ͜ͱ͕Ͱ͖ɼධ
Ձͷ޲্ʹ΋େ͖͘‫د‬༩͢Δͱߟ͑ΒΕΔɽ͜ΕΒͷ݁Ռ͸ɼද7஍ҬʹΑͬͯස౓ͷ܏޲͕มΘΔ୯‫ޠ‬ɽఏҊख๏ͷ༗ޮੑΛ͍ࣔͯ͠ΔɽΞϝϦΧ

5. 2 ஍ҬʹΑͬͯ܏޲͕มΘΔ୯‫ޠ‬ͯͷ݁ՌΛड़΂ɼߟ࡯ͨ͠ɽຊઅͰ͸ɼ‫ʹٯ‬஍ҬʹΑͬͯධՁinternet

156

261

167

110

35

214

wiﬁ

136

238

98

50

45

195

shopping-mall

78

128

65

62

19

170

shopping

76

296

264

277

126

634

ϗςϧͷ஍Ҭʢதࠃɼ೔ຊɼΞϝϦΧʣͰස౓ͷ܏޲͕ҟͳͬͨ୯‫ޠ‬Λද 7 ʹࣔ͢ɽ͜ΕΒʹ͍ͭͯɼස౓ͷ܏޲͕ҟͳͬͨཧ༝Λਪଌ͢Δɽinternet ΍ wiﬁ ͱ͍͏୯‫ޠ‬͸ɼΞϝϦΧͱ೔ຊͰ͸தࠃ‫Ͱޠ‬ɼதࠃͰ͸೔ຊ‫Ͱޠ‬ଟ͘ग़‫͍ͯ͠ݱ‬Δɽதࠃͷϗςϧʹ͓͍ͯ೔ຊ‫ޠ‬ͷϨϏϡʔΛௐࠪͨ͠ͱ͜Ζɼinternet
΍ wiﬁ ͱ͍͏୯‫ޠ‬ͷपΓʹ͸ʮ‫͕ܨ‬Βͳ͍ʯ΍ʮΞΫηεͰ͖ͳ͍ʯͱ͍ͬͨ୯‫͞ݟࢄ͕ޠ‬Εͨɽ͜Ε͸தࠃ੓෎ͷւ֎αΠτ΁ͷϒϩοΫߦҝͷෆຬͰ͋Γɼ͜ΕΛ೔தؒͷࠩͱ͢Δ͔͸ٞ࿦ͷ༨஍͕࢒Δ෦෼Ͱ͋Δɽ࣍ʹɼΞϝϦΧͱ೔ຊͰதࠃ‫ޠ‬ͷ਺͕૿͍͑ͯΔ఺ʹ͍ͭͯߟ͑Δɽதࠃਓ͸ւ֎ཱྀߦͷͱ͖ɼཱྀߦઌͰࡱӨͨࣸ͠ਅΛϒϩάͳͲʹΞοϓ͢Δ͜ͱ͕Α͋͘Δɽதࠃਓ͕தࠃʹ͍Δ৔߹͸ࣗ਎ͷ࣋ͭ௨৴‫ͰͲͳثػ‬͜ͷΑ͏ͳߦҝ͕ՄೳͰ͋Δ͕ɼւ֎Ͱ͸ࣗࠃͷ௨৴‫࢖͕ثػ‬͑ͳ͍৔߹΋ଟ͘ɼผ్ωοτϫʔΫ΁ͷ઀ଓ‫͕ڥ؀‬ඞཁʹͳ
Δͱߟ͑ΒΕΔɽͦͷ݁ՌɼΞϝϦΧ΍೔ຊͰϗςϧʹରͯ͠ωοτϫʔΫʹؔ࿈͢Δ‫͕ٴݴ‬ଟ͘ͳͬͨͷͩͱߟ͑ΒΕΔɽ

shopping ΍ shopping-mall ͱ͍͏୯‫͕ޠ‬தࠃʹ͋Δϗςϧͷ೔ຊ‫ͱޠ‬தࠃ‫ํ྆ޠ‬ͷϨϏϡʔͷग़‫ݱ‬ճ਺ͷࠩ͸΄ͱΜͲΈΒΕͳ͔͕ͬͨɼ೔ຊͱΞϝϦΧʹ͋Δϗςϧͷதࠃ‫ޠ‬ͷϨϏϡʔͰ͸ग़‫ݱ‬ස౓͕͔ͳΓ૿͍͑ͯͨɽ͜Ε͸ɼ‫ݩ‬ʑதࠃͷ੫͕ۚߴ͘ɼಉ͡঎඼ʹؔͯ͠ւ֎ͷ΄͏͕͍҆ͱ͍͏ࣄ৘͕͋Δɽͦͷ݁Ռɼւ֎ཱྀߦͷࡍɼγϣοϐϯάʹର͢Δؔ৺͕ߴ͘ͳΔͨΊͩͱߟ͑ΒΕΔɽ࠷ۙɼւ֎Ͱதࠃਓ͕രങ͍͢Δͱ͍͏χϡʔε΋Αࣖ͘ʹ͢Δ͜ͱ͔Βɼ‫ݪ‬Ҽͱͯ͠͸ೲಘͰ͖Δͱߟ͑ΒΕΔɽ

6. ͓ Θ Γ ʹຊ‫Ͱڀݚ‬͸ɼϗςϧϨϏϡʔΛର৅ͱͯ͠ɼ೔தؒͷධՁࠩҟΛ‫ݕ‬ग़͢Δख๏ʹ͍ͭͯड़΂ͨɽ࣮‫݁ݧ‬Ռ͔Βɼ೔ຊਓ͸ಛʹϗςϧͷαʔϏε΍‫ڥ؀‬ΛධՁ͠ɼதࠃਓ͸ϗςϧͷࢪઃ໘ΛධՁ͢Δ܏޲͕͋Δͱ͍͏ࠩҟΛ‫ݕ‬ग़Ͱ͖ͨɽಘΒΕͨࠩҟ೔ຊ‫ޠ‬೔ຊ

5. 2 અͰ͸஍ҬʹΑͬͯධՁͷ܏޲͕มΘΒͳ͍୯‫͍ͭʹޠ‬ͷ܏޲͕มΘͬͯ͠·ͬͨ୯‫͍ͯͭʹޠ‬ٞ࿦͢Δɽ೔ຊ‫ ޠ‬தࠃ‫ޠ‬தࠃ୯‫ޠ‬தࠃ‫ ޠ‬೔ຊ‫ޠ‬தࠃ‫ޠ‬ੑΛ֬ೝͨ͠ɽࠓճ͸࠷ऴతͳ݁Ռͷ෼ੳΛਓखͰߦͬͨɽ͜ͷΑ͏ͳ෼ੳΛΑΓ༰қʹߦ͏ͨΊʹ͸ɼಘΒΕͨ݁ՌͷՄࢹԽͳͲɼγεςϜͷΠϯλϑΣʔε͕ॏཁʹͳͬͯ͘ΔɽΑΓ࢖͍΍͘͢༗ޮͳ஌‫ݟ‬ΛಘΔͨΊͷࠩҟ‫ݕ‬ग़γεςϜͱͯ͠ͷ࿮૊ΈΛߟ࡯͢Δ͜ͱ͸ࠓ‫ޙ‬ͷॏཁͳ՝୊ͷ 1 ͭͰ͋Δɽຊ࿦จͰ͸ɼϗςϧͷϨϏϡʔΛର৅ͱͯࠩ͠ҟͷ෼ੳΛߦ͕ͬͨɼఏҊख๏͸ϗςϧʹಛԽͨ͠΋ͷͰ͸ͳ͘ɼ൚༻ੑͷ͋Δख๏Ͱ͋ΔɽධՁͷࠩҟ͸ϗςϧʹ‫ݶ‬Βͣଘࡏ͢Δͱߟ͑ΒΕΔͨΊɼଞͷ੡඼΍αʔϏεΛର৅ͱ࣮ͨ͠‫ݧ‬ɾ෼ੳɾߟ࡯΋‫ڵ‬ຯਂ͍՝୊Ͱ͋ΔɽఏҊख๏Ͱ͸ɼස౓ࠩͱ‫ײ‬৘ද‫ʹݱ‬ண໨͍ͯͨ͠ɽಛʹ‫ײ‬৘ද‫ݱ‬͸෼ੳͷͨΊʹ༗ޮͳཁૉͰ͋ΔɽҰํͰɼධՁΛ‫ؚ‬Ήจʹඞͣ໌ࣔతͳ‫ײ‬৘ද‫͕ݱ‬ଘࡏ͢Δͱ͸‫ݶ‬Βͳ͍ɽ‫ײ‬৘ද‫ݱ‬Λ‫ʹ҉͕͍ͳ·ؚ‬ධՁΛ͍ͯ͠Δจ΍ൺᄻ΍ൽ೑ͷΑ͏ͳ௚઀తͳධՁͰ͸ͳ͍จ΋ϨϏϡʔதʹ͸ଘࡏ͢Δɽ͜ͷΑ͏ͳ೉͍͠໰୊ʹରͯ͠ͲͷΑ͏ʹରԠ͢Δ͔΋ࠓ‫ޙ‬ͷॏཁͳ՝୊Ͱ͋Δɽจ‫ݙ‬[1] Bo Pang and Lillian Lee. Opinion mining and ɹ sentiment
analysis, Foundations and Trends in Information Retrieval,2(1-2), 2008.
[2] ਡ๚ஐେ, ‫ٶ‬෦ਅҥ, ٢໺޹. ೔ຊ‫ޠ‬൛ɾதࠃ‫ޠ‬൛ Wikipedia Λ༻͍ͨจԽࠩ‫ݕ‬ग़ख๏ͷఏҊ, ৘ใॲཧֶձ࿦จࢽ, Vol. 55, No.
1, pp. 257-266, 2014.
[3] த࡚‫׮‬೭, ઒৔ਅཧࢠ, ԣຊେี, Ӊ௡࿊෢ਔ, ෱‫ݪ‬஌޺. ଟ‫ޠݴ‬Wikipedia ΤϯτϦΛ஌ࣝ‫͢ͱݯ‬ΔಛఆτϐοΫͷ೔ӳϒϩάαΠτ‫ͱࡧݕ‬೔ӳର৅ϒϩά෼ੳ, ਓ޻஌ೳֶձ࿦จࢽ, Vol. 25,No. 5, 2010.
[4] Yinjun Hu and Yasuo Tanida. Using Twitter Data to Infer
Personal Values of Japanese Consumers, In Proceedings ofthe 29th Paciﬁc Asia Conference on Language, 2015.

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