本研究嘗試開(kāi)展社交媒體文本數(shù)據(jù)分析方法的對(duì)比研究，并揭示其在公園感知研究中的優(yōu)缺點(diǎn)和適用性。
互聯(lián)網(wǎng)科技和媒體的蓬勃發(fā)展產(chǎn)生了大量社交媒體數(shù)據(jù)，本研究嘗試開(kāi)展社交媒體文本數(shù)據(jù)分析方法的對(duì)比研究，并揭示其在公園感知研究中的優(yōu)缺點(diǎn)和適用性。研究選擇在相關(guān)領(lǐng)域廣泛應(yīng)用的詞典模型和LDA模型，以大眾點(diǎn)評(píng)網(wǎng)站上北京10座城市公園的點(diǎn)評(píng)文本為研究數(shù)據(jù)，分別從單個(gè)公園和公園整體使用感知兩個(gè)層面進(jìn)行文本分析，并對(duì)比分析感知主題的分類結(jié)果。結(jié)果表明：詞典模型更有利于在公園間進(jìn)行橫向?qū)Ρ确治?；LDA模型則可以直觀顯示公園特色和游客感知偏好；綜合運(yùn)用兩種模型可優(yōu)化公園感知評(píng)估。兩種方法揭示了北京城市公園游客對(duì)公園的關(guān)注主要集中于社交活動(dòng)的需求、自然景觀帶來(lái)的視覺(jué)審美需求，以及交通設(shè)施狀況和城市公園消費(fèi)情況。本研究既可為社交媒體文本分析方法的選擇和使用提供優(yōu)化建議，又可為公園建設(shè)與管理改進(jìn)提供依據(jù)與指導(dǎo)。
關(guān)鍵詞
社會(huì)感知；文本分析；詞典；隱含狄利克雷分布（LDA）；城市公園；景觀感知
社交媒體文本數(shù)據(jù)分析方法對(duì)比與適用性研究：以北京市城市公園感知為例
Comparison and Applicability Study of Analysis Methods for Social Media Text Data:
Taking Perception of Urban Parks in Beijing as an Example
北京大學(xué)建筑與景觀設(shè)計(jì)學(xué)院
隨著互聯(lián)網(wǎng)科技的高速發(fā)展，海量網(wǎng)絡(luò)媒體信息為社會(huì)感知的研究提供了數(shù)據(jù)基礎(chǔ)。這類研究早期多集中在通過(guò)簽到數(shù)據(jù)識(shí)別到訪率和動(dòng)機(jī)偏好分析，以及結(jié)合照片圖像內(nèi)容及其地理位置進(jìn)行的感知情緒分析。近年來(lái)，通過(guò)文本數(shù)據(jù)挖掘進(jìn)行感知分析的研究也開(kāi)始起步并日漸增多。通過(guò)文本數(shù)據(jù)進(jìn)行公園感知研究正逐漸受到學(xué)者們的關(guān)注。目前已經(jīng)可以通過(guò)建立文本分析模型來(lái)挖掘文本所呈現(xiàn)的內(nèi)在規(guī)律及主題，主題模型的運(yùn)用開(kāi)始成為感知分析和滿意度評(píng)價(jià)的基礎(chǔ)。已有研究在感知分析時(shí)，通常單獨(dú)采用其中一種模型進(jìn)行文本數(shù)據(jù)處理，鮮少探討不同模型之間的優(yōu)劣及專業(yè)適用性。
本研究嘗試開(kāi)展社交媒體文本數(shù)據(jù)分析方法的對(duì)比研究，并揭示其在公園感知研究中的適用性。由于基于詞典規(guī)則的分類分析模型（下文簡(jiǎn)稱“詞典模型”）和LDA模型在風(fēng)景名勝區(qū)和城市公園感知研究中應(yīng)用廣泛，本研究針對(duì)二者展開(kāi)對(duì)比分析。本研究聚焦于以下問(wèn)題：在對(duì)基于公園感知的社交媒體文本進(jìn)行分析時(shí)，詞典模型和LDA模型的感知研究過(guò)程與分析結(jié)果存在怎樣的差異？?jī)煞N模型的優(yōu)劣是什么？此基礎(chǔ)上，研究團(tuán)隊(duì)進(jìn)一步探究如何利用兩種模型的優(yōu)勢(shì)為城市公園規(guī)劃提供指導(dǎo)，并總結(jié)文本分析方法在公園感知研究中的適用價(jià)值。
研究區(qū)域概況與數(shù)據(jù)來(lái)源
北京市市域擁有各類公園1050個(gè)，公園綠地面積累計(jì)達(dá)357.2km2。本研究選擇大眾點(diǎn)評(píng)網(wǎng)作為文本數(shù)據(jù)來(lái)源，使用Python軟件中的Request模塊獲取北京市公園目錄下自2006年4月至2020年9月的所有文字點(diǎn)評(píng)數(shù)據(jù)和點(diǎn)評(píng)者信息，選取點(diǎn)評(píng)數(shù)量排名前10位的城市公園作為研究對(duì)象（表1）。
為保證模型分析的準(zhǔn)確性，研究對(duì)數(shù)據(jù)進(jìn)行了預(yù)處理，僅保留字符數(shù)大于50的文本數(shù)據(jù)。篩選后評(píng)價(jià)數(shù)量最少的公園為北京園博園（6531條），以此為標(biāo)準(zhǔn)使用SPSS分別對(duì)其他各個(gè)公園的評(píng)價(jià)數(shù)據(jù)進(jìn)行完全隨機(jī)抽樣，最終獲得65310條點(diǎn)評(píng)文本數(shù)據(jù)。研究選用Python語(yǔ)言工具jieba分詞對(duì)數(shù)據(jù)進(jìn)行分詞。清洗文本數(shù)據(jù)進(jìn)并進(jìn)行同義詞替換。根據(jù)實(shí)際使用情況，人工篩查及調(diào)整分詞和同義詞替換結(jié)果，還原不恰當(dāng)?shù)耐x詞替換內(nèi)容。
詞典模型采用王志芳等人于2021年提出的基于景觀服務(wù)的城市公園感知主題分類評(píng)估模型，該模型經(jīng)過(guò)詞典有效性檢驗(yàn)，整體性能測(cè)試結(jié)果優(yōu)良。在本研究中，運(yùn)用Python對(duì)預(yù)處理后的數(shù)據(jù)進(jìn)行結(jié)構(gòu)化處理并提取高頻詞；之后進(jìn)行人工分類，構(gòu)建中文景觀服務(wù)感知詞典；繼而利用Word2vec和人工添加的方式擴(kuò)建詞典內(nèi)容，并劃分到不同的感知主題類別中。根據(jù)已有的文獻(xiàn)研究，共劃分出9類含義不同的公園景觀服務(wù)感知主題（表2）。
將獲取的公園感知評(píng)價(jià)文本數(shù)據(jù)與詞典進(jìn)行匹配，以此識(shí)別評(píng)價(jià)數(shù)據(jù)中的用詞，進(jìn)而提取出單條評(píng)價(jià)中所涉及的感知主題計(jì)算各類主題的感知頻率。將涉及某項(xiàng)感知主題的評(píng)論數(shù)量與總評(píng)論數(shù)量的比值作為相應(yīng)景觀服務(wù)主題在該公園的感知頻率。
LDA是一種通過(guò)計(jì)算機(jī)來(lái)自動(dòng)分析文本的語(yǔ)言處理模型，能夠快速?gòu)姆墙Y(jié)構(gòu)化文本（即文檔）中提煉出主題。LDA模型可以計(jì)算“文檔－主題”和“主題－詞語(yǔ)”兩類概率分布，從而實(shí)現(xiàn)對(duì)文檔主題和對(duì)應(yīng)詞語(yǔ)（關(guān)鍵詞）的分類。
本研究使用Python軟件的gensim工具包調(diào)用LDA模型，實(shí)現(xiàn)文本數(shù)據(jù)主題分析。本研究中的主題數(shù)量主要通過(guò)計(jì)算主題一致性得分來(lái)確定，最后結(jié)合人工對(duì)一致性得分較高的主題進(jìn)行篩選，確定合適的主題數(shù)量以獲得理想的模型運(yùn)算結(jié)果。獲得結(jié)果后，對(duì)于每個(gè)主題的實(shí)際權(quán)重進(jìn)行計(jì)算。針對(duì)每個(gè)公園的結(jié)果，分別進(jìn)行主題命名，同時(shí)去除權(quán)重較低且感知內(nèi)容相關(guān)性較弱的主題，即“噪聲”主題。
對(duì)兩種模型得到的不同感知主題的分布進(jìn)行相關(guān)性分析。不同感知主題在每條評(píng)價(jià)文本中的分布情況為二分類變量，結(jié)果為“是”／“否”（分別記為“1”／“0”）兩項(xiàng)，因此在SPSS軟件中計(jì)算Phi系數(shù)，進(jìn)行相關(guān)性檢驗(yàn)。
本研究使用Python對(duì)評(píng)價(jià)文本進(jìn)行詞頻分析，通過(guò)詞云圖表達(dá)不同文本數(shù)據(jù)中被使用者提及頻次較高的詞語(yǔ)內(nèi)容，以獲取各公園的感知主題內(nèi)容。
本研究基于北京市10座城市公園的大眾點(diǎn)評(píng)評(píng)價(jià)文本數(shù)據(jù)，利用兩種模型分別從單個(gè)公園和公園整體使用感知兩個(gè)層面進(jìn)行文本分析，并對(duì)比分析感知主題的分類結(jié)果。
研究技術(shù)路線圖 ? 尚珍宇，程可欣，簡(jiǎn)鈺清，王志芳
詞典模型分類統(tǒng)計(jì)結(jié)果顯示，游客對(duì)各公園不同主題的感知頻率存在明顯差異：圓明園遺址公園和奧林匹克森林公園的感知總頻率最高，北京世界公園與朝陽(yáng)公園的感知總頻率相對(duì)較低；奧林匹克森林公園不同主題間感知頻率差異最大。此外，在不同公園中，娛樂(lè)活動(dòng)和美學(xué)欣賞均表現(xiàn)出較高的游客感知頻率，教育價(jià)值和宗教信仰的感知頻率普遍較低。圓明園遺址公園在歷史文化方面的感知頻率、八大處公園在宗教信仰方面的感知頻率、景山公園的美學(xué)欣賞感知頻率、朝陽(yáng)公園的社會(huì)交往感知頻率明顯高于其他公園。除此之外，玉淵潭公園和八大處公園的教育價(jià)值感知關(guān)注度相較于其他公園有所不足。
詞典模型下各公園不同主題的感知頻率差異圖 ? 尚珍宇，程可欣，簡(jiǎn)鈺清，王志芳
由LDA模型下的感知分析結(jié)果可知，北京市10座城市公園的感知類型差異明顯，社交媒體評(píng)價(jià)突出體現(xiàn)了公園自身的景觀特色和游客感知偏好。通過(guò)表3可以看出，不同公園游客感知的主題數(shù)量普遍被分為8或9項(xiàng)，其中圓明園遺址公園、玉淵潭公園和奧林匹克森林公園的感知主題較多，北京世界公園最少。在感知內(nèi)容上公園間存在差異，但部分主題在多數(shù)公園中均有體現(xiàn)。除此之外，部分感知主題因公園自身的特色表現(xiàn)出不同。同時(shí)，節(jié)慶活動(dòng)在不同公園中也會(huì)產(chǎn)生獨(dú)特的游客感知。
玉淵潭公園主題詞云圖 ? 尚珍宇，程可欣，簡(jiǎn)鈺清，王志芳
香山公園主題詞云圖 ? 尚珍宇，程可欣，簡(jiǎn)鈺清，王志芳
將10座公園的所有評(píng)論文本數(shù)據(jù)進(jìn)行LDA模型分析，結(jié)果顯示，感知主題可劃分為10項(xiàng)，其中交通門(mén)票、春季景觀、記憶感知和社交活動(dòng)的感知頻率高于其他主題，登山活動(dòng)、人文歷史、集會(huì)表演、秋季景觀、宗教文化、特色建筑的感知頻率相對(duì)較低。由此可見(jiàn)，北京城市公園游客對(duì)公園的關(guān)注主要集中于社交活動(dòng)的需求、自然景觀帶來(lái)的視覺(jué)審美需求，以及交通設(shè)施狀況和城市公園消費(fèi)情況。
綜合分析結(jié)果可以看出北京城市公園游客主要關(guān)注社交游憩需求和自然景觀帶來(lái)的視覺(jué)審美需求是否得到滿足，同時(shí)對(duì)交通設(shè)施狀況和城市公園消費(fèi)情況較為敏感。基于詞典模型的9項(xiàng)感知主題和LDA模型的10項(xiàng)感知主題在評(píng)價(jià)中的分布具有一定的相關(guān)性，主題分布相關(guān)性較強(qiáng)的有：春季景觀與環(huán)境改善、生物多樣性、娛樂(lè)活動(dòng)和美學(xué)欣賞；宗教文化與歷史文化、宗教信仰；登山活動(dòng)與宗教信仰；秋季景觀與美學(xué)欣賞；社交活動(dòng)與娛樂(lè)活動(dòng)、社會(huì)交往；記憶感知與教育價(jià)值；人文歷史與歷史文化、美學(xué)欣賞和教育價(jià)值。除此之外，詞典模型下的身心修復(fù)主題，以及LDA模型下的交通門(mén)票、特色建筑及集會(huì)表演主題與其他感知主題的分布相關(guān)性都較弱。
兩種模型下不同感知主題相關(guān)性?；鶊D ? 尚珍宇，程可欣，簡(jiǎn)鈺清，王志芳
兩種模型感知內(nèi)容分類的結(jié)果均表現(xiàn)出對(duì)自然景觀、人文歷史景觀和娛樂(lè)活動(dòng)的關(guān)注。此外，LDA模型的分類結(jié)果更側(cè)重于對(duì)不同自然景觀和游覽活動(dòng)的綜合感知；同時(shí)，將娛樂(lè)活動(dòng)劃分為更具體的主題。相比于詞典模型清晰的感知主題劃分，LDA模型的分析結(jié)果界限相對(duì)模糊。
兩種模型下的游客感知主題類型在不同公園的表現(xiàn)存在明顯差異。在單個(gè)公園的分析中所獲取的感知主題類型存在明顯差異。LDA模型提煉出的感知主題在不同公園中體現(xiàn)的內(nèi)容各有不同，例如祭拜活動(dòng)和登山活動(dòng)等主題僅在個(gè)別公園中有所呈現(xiàn)；幾乎未能呈現(xiàn)低頻感知的內(nèi)容；主題更加突出公園自身的特色，類型更加細(xì)分，且存在部分詞典模型未涉及的感知內(nèi)容。相比之下，詞典模型則能夠捕捉到所有設(shè)定的感知內(nèi)容。感知主題與涵蓋內(nèi)容受現(xiàn)有詞典的影響，分類分析結(jié)果更加注重游客對(duì)人工選定的不同景觀服務(wù)內(nèi)容的感知，識(shí)別到的對(duì)周邊環(huán)境和景觀要素的感知較少。
兩種模型在公園感知文本分析中的優(yōu)缺點(diǎn)
通過(guò)對(duì)比分析可以看出，基于詞典模型和LDA模型的城市公園感知分析在主題類型劃分上具有顯著差異?？蓮墓珗@感知類型劃分、感知內(nèi)容識(shí)別及模型適用范圍梳理兩種方法的具體優(yōu)缺點(diǎn)（表4）。
在模型優(yōu)化方面，可以基于LDA分析結(jié)果對(duì)詞典模型的詞典內(nèi)容進(jìn)行擴(kuò)充、完善。在模型專業(yè)適用性方面，可以結(jié)合兩者特點(diǎn)和優(yōu)勢(shì)來(lái)判斷結(jié)合應(yīng)用的途徑。進(jìn)行區(qū)域尺度的公園感知分析時(shí)，可先利用詞典模型進(jìn)行現(xiàn)狀分析，為公園的建設(shè)、管理和改進(jìn)提供依據(jù)；再選定需要深入挖掘的感知類型，通過(guò)LDA模型進(jìn)行具體的文本分析，細(xì)化公園感知內(nèi)容。對(duì)于單個(gè)公園進(jìn)行感知分析時(shí)，可以基于LDA模型的結(jié)果確定公園的特色和游客的關(guān)注內(nèi)容，再據(jù)此優(yōu)化詞典模型并展開(kāi)進(jìn)一步分析，以期更加全面地發(fā)現(xiàn)問(wèn)題。
本研究選擇了兩種最常用的文本主題分析模型——詞典模型與LDA模型，對(duì)相同的研究對(duì)象進(jìn)行分析，探討兩種模型的應(yīng)用在城市公園感知研究中的差異，以明確其優(yōu)缺點(diǎn)和優(yōu)化途徑。研究結(jié)果不僅對(duì)城市公園的建設(shè)和管理具有指導(dǎo)性價(jià)值，也有利于推進(jìn)通過(guò)文本分析進(jìn)行社會(huì)感知的相關(guān)研究發(fā)展。
本研究仍存在一定的局限性。在數(shù)據(jù)來(lái)源方面，來(lái)自大眾點(diǎn)評(píng)網(wǎng)站的評(píng)價(jià)文本缺乏使用者的個(gè)人信息，無(wú)法進(jìn)行有效的用戶畫(huà)像分析，分析結(jié)果難以全面體現(xiàn)城市公園游客感知情況。此外，LDA模型作為傳統(tǒng)的無(wú)監(jiān)督分類模型，無(wú)法把控分類結(jié)果。針對(duì)LDA模型問(wèn)題目前已有改進(jìn)的涉及半監(jiān)督和有監(jiān)督的機(jī)器學(xué)習(xí)主題分類模型，有待進(jìn)一步探究。最后，除了本文所探究的兩種模型外，基于大數(shù)據(jù)的文本分類模型還有多種，不同的模型算法具有各自的優(yōu)勢(shì)和不足，后續(xù)研究也需要結(jié)合更多模型進(jìn)行進(jìn)一步的深化和驗(yàn)證。
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本文引用格式 / PLEASE CITE THIS ARTICLE AS
Shang, Z., Cheng, K., Jian, Y., & Wang, Z. (2023). Comparison and applicability study of analysis methods for social media text data: Taking perception of urban parks in Beijing as an example. Landscape Architecture Frontiers, 11(5), 8?29. https://doi.org/10.15302/J-LAF-1-020083
編輯 | 王穎，周佳怡
翻譯 | 王穎，尚珍宇，周佳怡
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