以中国国家博物馆为案例地,以去哪儿网站抓取的网络评论文本为研究素材,利用ROST CM6软件,采取内容分析法和社会网络分析法,从高频特征词、语义网络、情感评价三方面研究影响游客体验的要素结构。结果表明:1) “国家”“预约”“历史”...以中国国家博物馆为案例地,以去哪儿网站抓取的网络评论文本为研究素材,利用ROST CM6软件,采取内容分析法和社会网络分析法,从高频特征词、语义网络、情感评价三方面研究影响游客体验的要素结构。结果表明:1) “国家”“预约”“历史”词频次数靠前,在整个博物馆旅游体验中极其重要。2) 评论文本呈现出以“展览、文物、文化、预约、门票”多个核心高频词为中心,表现出整体分散、局部集中的特点。3) 由于存在预约难、电子讲解不智能、游览盲目性导致时间浪费无法参观更多文物等问题,从而导致积极情绪程度中的高度情绪不高。This study took the National Museum of China as a case and utilized online review texts collected from the Qunar website as research material. Using ROST CM6 software, content analysis and social network analysis methods were employed to investigate the structural factors influencing tourist experiences from three aspects: high-frequency characteristic words, semantic networks, and sentiment evaluation. The results indicate that: 1) The words “national”, “reservation”, and “history” appear with high frequency, underscoring their critical importance in the overall museum tourism experience;2) The review texts demonstrate a pattern characterized by multiple core high-frequency words such as “exhibition”, “relics”, “culture”, “reservation” and “tickets”, which exhibit a general dispersal with localized concentration;3) Issues such as difficulties in making reservations, the lack of intelligence in electronic guides, and the aimlessness of tours leading to wasted time and fewer opportunities to view more relics contribute to a low level of high-intensity positive emotions.展开更多
一、“神官小像”资料介绍《古代バクドリア遗宝展図绿》中刊布有六尊“神官小像”,它们分别为:48a、48b、48c、48d以及49a、49b①。《古代バクドリア遗宝展図绿》集结了名为“Treasure of Ancient Bactria”展览中的展品,这次展览是日...一、“神官小像”资料介绍《古代バクドリア遗宝展図绿》中刊布有六尊“神官小像”,它们分别为:48a、48b、48c、48d以及49a、49b①。《古代バクドリア遗宝展図绿》集结了名为“Treasure of Ancient Bactria”展览中的展品,这次展览是日本Miho Museum为了庆祝开馆五周年举办的一场特展,展品来自塔吉克斯坦国家博物馆。展开更多
文摘以中国国家博物馆为案例地,以去哪儿网站抓取的网络评论文本为研究素材,利用ROST CM6软件,采取内容分析法和社会网络分析法,从高频特征词、语义网络、情感评价三方面研究影响游客体验的要素结构。结果表明:1) “国家”“预约”“历史”词频次数靠前,在整个博物馆旅游体验中极其重要。2) 评论文本呈现出以“展览、文物、文化、预约、门票”多个核心高频词为中心,表现出整体分散、局部集中的特点。3) 由于存在预约难、电子讲解不智能、游览盲目性导致时间浪费无法参观更多文物等问题,从而导致积极情绪程度中的高度情绪不高。This study took the National Museum of China as a case and utilized online review texts collected from the Qunar website as research material. Using ROST CM6 software, content analysis and social network analysis methods were employed to investigate the structural factors influencing tourist experiences from three aspects: high-frequency characteristic words, semantic networks, and sentiment evaluation. The results indicate that: 1) The words “national”, “reservation”, and “history” appear with high frequency, underscoring their critical importance in the overall museum tourism experience;2) The review texts demonstrate a pattern characterized by multiple core high-frequency words such as “exhibition”, “relics”, “culture”, “reservation” and “tickets”, which exhibit a general dispersal with localized concentration;3) Issues such as difficulties in making reservations, the lack of intelligence in electronic guides, and the aimlessness of tours leading to wasted time and fewer opportunities to view more relics contribute to a low level of high-intensity positive emotions.
文摘一、“神官小像”资料介绍《古代バクドリア遗宝展図绿》中刊布有六尊“神官小像”,它们分别为:48a、48b、48c、48d以及49a、49b①。《古代バクドリア遗宝展図绿》集结了名为“Treasure of Ancient Bactria”展览中的展品,这次展览是日本Miho Museum为了庆祝开馆五周年举办的一场特展,展品来自塔吉克斯坦国家博物馆。
