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1.
Understanding the geographical preferences of international tourists is critical for the tourism planning and marketing. However, it is not an easy endeavor to gather the corresponding information, given the absence of city-level tourism statistical data and high costs of participant survey. This paper characterizes the geographical preferences of international tourists using geo-tagged photos on social media (the Flickr in particular). Data are harvested for 333 prefecture-level cities in China from 2008 to 2013, and the intensity of photo sharing (IPS: the ratio between total number of uploaded photos and total area of the city/region) is used an indicator of tourist geographical preferences. IPS visualization shows the geography that tourism hotpots generally concentrate in regional capital cities and economically developed megaregions. More specifically, the East Asia and Oceania tourists exhibit more preferences towards the eastern coastal cities, while the Europe and North America visitors show increasing interest in exploring the western and northern places. Spatial regression is employed to quantify the local influential factors of tourists’ geographical preferences. It is found that international tourists usually consider the local economy, accessibility, infrastructure and cultural attractions when they choose their destinations in China. East Asia and Oceania visitors particularly appreciate the local economy and cultural attractions. Europe and North America tourists especially value the cultural attractions and local openness. The demonstrated methodological framework is not restricted to Flickr data, and it can be applicable to social media offer geo-tagging service. This paper is therefore believed to advance the applications of social media into geographical research. 相似文献
2.
Lin Wan Zhou Huang Xia Peng Ran Li 《International journal of geographical information science》2018,32(11):2225-2246
Geo-tagged travel photos on social networks often contain location data such as points of interest (POIs), and also users’ travel preferences. In this paper, we propose a hybrid ensemble learning method, BAyes-Knn, that predicts personalized tourist routes for travelers by mining their geographical preferences from these location-tagged data. Our method trains two types of base classifiers to jointly predict the next travel destination: (1) The K-nearest neighbor (KNN) classifier quantifies users’ location history, weather condition, temperature and seasonality and uses a feature-weighted distance model to predict a user’s personalized interests in an unvisited location. (2) A Bayes classifier introduces a smooth kernel function to estimate a-priori probabilities of features and then combines these probabilities to predict a user’s latent interests in a location. All the outcomes from these subclassifiers are merged into one final prediction result by using the Borda count voting method. We evaluated our method on geo-tagged Flickr photos and Beijing weather data collected from 1 January 2005 to 1 July 2016. The results demonstrated that our ensemble approach outperformed 12 other baseline models. In addition, the results showed that our framework has better prediction accuracy than do context-aware significant travel-sequence-patterns recommendations and frequent travel-sequence patterns. 相似文献
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4.
Pengfei Chen Xiaolin Zhou Zhewei Liu Xuandi Fu 《International journal of geographical information science》2013,27(12):2337-2362
ABSTRACTAn increasing number of social media users are becoming used to disseminate activities through geotagged posts. The massive available geotagged posts enable collections of users’ footprints over time and offer effective opportunities for mobility prediction. Using geotagged posts for spatio-temporal prediction of future location, however, is challenging. Previous studies either focus on next-place prediction or rely on dense data sources such as GPS data. Introduced in this article is a novel method for future location prediction of individuals based on geotagged social media data. This method employs the hierarchical density-based clustering algorithm with adaptive parameter selection to identify the regions frequently visited by a social media user. A multi-feature weighted Bayesian model is then developed to forecast users’ spatio-temporal locations by combining multiple factors affecting human mobility patterns. Further, an updating strategy is designed to efficiently adjust, over time, the proposed model to the dynamics in users’ mobility patterns. Based on two real-life datasets, the proposed approach outperforms a state-of-the-art method in prediction accuracy by up to 5.34% and 3.30%. Tests show prediction reliability is high with quality predictions, but low in the identification of erroneous locations. 相似文献
5.
People’s behavior on online social networks, which store geo-tagged information showing where people were or are at the moment, can provide information about their offline life as well. In this paper we present one possible research direction that can be taken using Flickr dataset of publicly available geo-tagged media objects (e.g., photographs, videos). Namely, our focus is on investigating attractiveness of countries or smaller large-scale composite regions (e.g., US states) for foreign visitors where attractiveness is defined as the absolute number of media objects taken in a certain state or country by its foreign visitors compared to its population size. We also consider it together with attractiveness of the destination for the international migration, measured through publicly available dataset provided by United Nations. By having those two datasets, we are able to look at attractiveness from two different perspectives: short-term and long-term one. As our previous study showed that city attractiveness for Spanish cities follows a superlinear trend, here we want to see if the same law is also applicable to country/state (i.e., composite regions) attractiveness. Finally, we provide one possible explanation for the obtained results. 相似文献
6.
城市旅游感知意象与投射意象的匹配程度是城市旅游形象建设与宣传效果的重要评价,景观尺度下旅游感知与投射意象的空间分异特征可以有效评估游客对城市旅游意象的感知偏差,以此把握旅游者的旅游动机与景观偏好,更好地提升旅游地形象建设。本研究以五大世界著名旅游城市为例,以Flickr网站的地理标记照片数据和政府旅游网站宣传的旅游信息为数据源,利用ArcGIS空间分析技术分析城市旅游感知意象与投射意象的要素构成和空间分异特征。结果表明,城市旅游感知与投射意象的差异既体现在要素构成的偏差上,也体现在空间分布特征的差异方面。除东京旅游感知与投射意象要素结构基本一致以外,其他城市均存在一定程度的偏差。局部空间聚集异常值可视化了五大城市旅游感知意象与投射意象的空间分布偏差,相比城市旅游投射意象的空间集聚,城市旅游感知意象的范围更为离散。同时,双变量空间自相关指数分析结果验证了五大城市旅游感知意象与投射意象均呈显著的空间正相关,但是相关程度和依赖度并不高,说明了从感知与投射视角进行旅游意象空间特征分析的重要性,应以需求为导向进行城市旅游景观规划与宣传。结合地理标记照片数据的空间分析方法为城市旅游感知意象与投射意象的空间分异研究提供了普适性的方法,以服务于城市可持续发展和旅游形象建设。 相似文献
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随着消费级无人机技术的快速发展,无人机航拍摄影资料成为城市形象感知研究的重要数据来源。论文基于社交平台“天空之城”获取的西安市无人机航拍照片、简介文本和拍摄地位置等信息,综合运用计算机视觉图片分析、计算机文本情感分析、社会网络分析和GIS空间分析等方法,探究无人机视角下的西安城市形象。研究发现:① 无人机航拍照片主要集中在主城区,周边郊县较为疏散,呈现“内密外疏”的空间格局,其核密度最高值区位于三区交界的城市中心地带,为南北向的“哑铃型”布局;② 视觉形象侧重对现代城市景观的描述,以人文景观类照片为最;③ 情感评价整体趋于积极正向,在主城区热门景点两极分化明显。最后,探索了无人机视角下城市形象建构与提升的综合机制,并对西安城市形象建设和无人机使用政策提出优化建议。 相似文献
8.
生活美学时代,旅游与生活交织在一起,旅游者的需求和行为正在从匆忙的景观凝视向多元的生活方式转变。生活风格是一种整体偏好,塑造个体的生活模式和行为习惯。旅游活动呈现强烈的情感消费特征。采用结构方程建模方法（SEM）,以情绪评价理论为基础,选择西安大唐芙蓉园为案例地,探讨生活风格通过情感中介变量对游客旅游照片分享行为的影响机制。结果显示：1）生活风格对游客旅游照片分享行为具有不显著的负向影响,在旅游仪式感和自我认同感的中介作用下,对游客旅游照片分享行为产生重要间接影响。2）生活风格对游客的旅游仪式感、真实性感知和自我认同感均具有显著正向影响。3）旅游仪式感、自我认同感对游客旅游照片分享行为有显著正向影响,在生活风格和游客旅游照片分享行为之间发挥中介作用。4）真实性感知对游客旅游照片分享行为具有不显著正向影响,未在生活风格和游客旅游照片分享行为之间发挥中介作用。 相似文献
9.
Coupling maximum entropy modeling with geotagged social media data to determine the geographic distribution of tourists 总被引：1，自引：0，他引：1
Yingwei Yan Chiao-Ling Kuo Chen-Chieh Feng Wei Huang Alexander Zipf 《International journal of geographical information science》2018,32(9):1699-1736
Modeling the geographic distribution of tourists at a tourist destination is crucial when it comes to enhancing the destination’s resilience to disasters and crises, as it enables the efficient allocation of limited resources to precise geographic locations. Seldom have existing studies explored the geographic distribution of tourists through understanding the mechanisms behind it. This article proposes to couple maximum entropy modeling with geotagged social media data to determine the geographic distribution of tourists in order to facilitate disaster and crisis management at tourist destinations. As one of the most popular tourist destinations in the United States, San Diego was chosen as the study area to demonstrate the proposed approach. We modeled the tourist geographic distribution in the study area by quantifying the relationship between the distribution and five environmental factors, including land use, land parcel, elevation, distance to the nearest major road and distance to the nearest transit stop. The geographic distribution’s dependency on and sensitivity to the environmental factors were uncovered. The model was subsequently applied to estimate the potential impacts of one simulated tsunami disaster and one simulated traffic breakdown due to crisis events such as a political protest or a fire hazard. As such, the effectiveness of the approach has been demonstrated with specific disaster and crisis scenarios. 相似文献
10.
Mario Cardozo 《The Professional geographer》2013,65(3):443-446
Web 2.0 has yielded a wealth of publicly available data, largely through the popularization of social media and the proliferation of user-generated content (UGC). Thus, the data void in social science research is diminishing as these new data sources are exploited. The discipline of geography, in particular, stands to benefit considerably from geotagged UGC or volunteered geographic information (VGI). In this article, we utilize a form of UGC—restaurant reviews—to evaluate the geography of Web 2.0 in Franklin County, Ohio. We find that restaurant reviews are largely concentrated in relatively few areas of the city, indicating that the impacts of Web 2.0 have not touched down evenly within the central county of the Columbus metropolitan statistical area. We argue that an intraurban digital divide is still apparent and might even be exacerbated by Web 2.0. 相似文献
11.
随着旅游活动大众化,游客拥挤愈发常态化。全面梳理游客拥挤的研究进展对于强化游客管理、促进旅游业高质量发展具有重要意义。从游客拥挤的内涵、测度、生成机制、影响因素、作用效果等多个角度进行文献梳理,研究发现:1)游客拥挤是游客对所处游览环境的负面评价,是对空间拥挤和人群拥挤的消极感知,刺激超载理论、社会干预理论及期望理论对游客拥挤的生成具有较好的解释效应;2)游客拥挤感存在明显差异,该差异主要来源于个体、空间场景及人群环境等因素,社会认同理论、唤醒理论、规范理论及曼宁理论能够有效解释游客拥挤感知差异的生成;3)游客拥挤易对游客情感、旅游满意度与忠诚度产生负面影响,易引发产品转换、合理化、置换等调试行为。今后研究可结合时空情境,关注游客拥挤的差异化测量、识别影响游客拥挤的关键因素以及探明游客拥挤的多元影响,如游客拥挤对景区管理、目的地规划布局、旅游可持续发展的影响。 相似文献
12.
《The Professional geographer》2013,65(4):422-433
Abstract Analyses of criminals' travel patterns can provide significant suggestions to improve crime management. This study extends the investigation of criminals' travel behavior from journey-to-crime to journey-after-crime. Moreover, new methods are developed to examine the spatial patterns of location pairs when restricted by the underlying geographical process. The methods are employed to investigate criminals' journey-after-auto-theft in the city of Buffalo, New York. The analyses reveal that auto thieves' trips from vehicle-theft locations to the corresponding vehicle-recovery locations are local in nature. The travel distances are significantly shorter than the randomly simulated trips; the travel directions are biased from the random directions as well. 相似文献
13.
不同出游时间视角下游客流动网络结构及其分异特征——以西安市为例 总被引：1，自引：0，他引：1
以热门旅游城市西安市为研究区域,采集网络游记数据,综合运用社会网络分析和GIS空间分析方法,探讨不同出游时间下的游客流动网络结构及其分异特征,研究发现：① 不同的出游时间约束下,游客旅游出行行为表现出显著的时间异质性。② 基于游客流动的西安市旅游吸引物的节点结构具有显著的等级规模分异特征,随着出游时间的增加,旅游节点等级结构体系呈现出以高等级景点为枢纽的“强强”关联特征,高等级景点的游客集聚功能提升显著。③ 随着出游时间增加,西安市区旅游节点核心?边缘结构越明显,核心区的节点联系强度越大,区位邻近、知名度接近与交通便利是形成景点组团的关键因子。 相似文献
14.
Yongmei Lu 《The Professional geographer》2003,55(4):422-433
Analyses of criminals' travel patterns can provide significant suggestions to improve crime management. This study extends the investigation of criminals' travel behavior from journey‐to‐crime to journey‐after‐crime. Moreover, new methods are developed to examine the spatial patterns of location pairs when restricted by the underlying geographical process. The methods are employed to investigate criminals' journey‐after‐auto‐theft in the city of Buffalo, New York. The analyses reveal that auto thieves' trips from vehicle‐theft locations to the corresponding vehicle‐recovery locations are local in nature. The travel distances are significantly shorter than the randomly simulated trips; the travel directions are biased from the random directions as well. 相似文献
15.
游客旅游后的城市形象和重游意愿的研究较多，却忽视了在旅游前对城市形象和旅游意愿的研究，本文尝试建立旅游前的异地展览会推广对城市形象与旅游意愿影响的模型。以“活力澳门推广周-长沙站”为研究样本，采用以非随机抽样的方式收集到393份有效问卷并进行分析。研究发现异地展览会对城市形象及旅游意愿具有显著正向影响，旅游前的城市形象对旅游意愿具有显著正向影响，而异地展览推广在城市形象与旅游意愿间存在着显著中介效应。因而，异地展览提供给人们对城市形象另一种了解认知的方式，成为影响人们旅游决策的因素之一，对城市形象和旅游推广起到重要作用。 相似文献
16.
《Urban geography》2013,34(5):373-396
Attention has been devoted to the globalization of international property investments during the 1980s and the role of Japanese investors in major financial centers and tourist resorts. This research seeks to establish how the locational preferences of Japanese investors in North American real estate markets were established. It utilizes a survey of 39 Japanese investment companies, together with important secondary data on investment outcomes, and distinguishes a number of ways in which information concerning overseas real estate investment opportunities was reviewed by decision makers in Japan. The results show that Japanese investors, far from being footloose, had fairly fixed locational preferences, were tied to a restricted range of centers (mainly New York, Los Angeles, and Hawaii), and hesitated to expand into a wider range of locations even after some time. Japanese investor behavior is shown to have ramifications for “world city” theory. 相似文献
17.
大数据时代,社交媒体的大量应用为研究游客情感体验以及探索其时空变化提供了新的数据源。采集3 a间西安市国内游客微博签到数据,运用热点格网图法、Getis-Ord Gi*方法和X-means聚类方法,从积极情感和消极情感2个维度研究西安市国内游客情感体验时空变化和演化规律。结果表明：（1） 城市中心、城市主轴线、主要商圈以及景区景点附近游客情感相对较高且稳定,高情感体验区域主要分布在曲江新区和西安古城旅游区。（2） 消极情感体验在西安的交通枢纽和城市边缘的空间占比高,交通枢纽主要以车站、城市进出口为主。（3） 整体上来看,3 a间西安市游客情感较为平稳,积极情感呈现“中心—边缘”的空间格局,消极情感和积极情感的呈现具有相似性,主要以3种类型为主：稳定型、相对稳定型和剧烈波动型。在3种类型中,稳定型的主要聚集地在城市中心、商圈附近、交通干线周边以及景区景点附近,相对稳定型占据西安市大面积区域,剧烈波动型处于距离城市中心较远的边缘。 相似文献
18.
Conventional ways of trip planning using online reviews from multiple sources are often cumbersome and uncustomizable. The advance in information and communication technology (ICT) and the surge in user-generated contents (UGC) provide great opportunities to facilitate trip planning. This paper proposes a travel-planning tool by crowdsourcing multiple UGCs to provide customized information for tourists. We harvested hotel customer reviews from TripAdvisor, photo information from Flickr, and travel costs between destinations from Uber. First, we used geospatial data mining approaches to extract tourism attractions information from Flickr; identified multi-facet characteristics of hotels with natural language processing (NLP); and provided travel route recommendations with graph analysis. Second, we developed a web-based interface to let users communicate with the system interactively, which provides integrated recommendations including attractions, hotels, and visit route sequences. Two cities in the United States (i.e. Atlanta and Chicago) were used as cases to illustrate our approaches. The proposed travel planning tool is not only beneficial to support customized travel decision-making, but also supportive for hotel managers with strategic management implications. 相似文献
19.
基于地理标记照片的北京市入境旅游流空间特征 总被引：11，自引：1，他引：10
城市作为现代旅游目的地的一种重要类型,在集聚旅游发展要素、塑造城市休闲空间、提升城市品质等方面具有突出作用。城市旅游流是城市旅游要素关联、空间组织的路径,对于城市交通组织方式、公共服务设施建设、休闲旅游产业布局等方面影响越来越大。本文立足城市内部微观尺度,以入境旅游流空间特征为研究对象,利用数据挖掘技术,通过Flickr API接口获取了2004-2015年北京市范围内全部带有地理信息的照片及其属性信息,通过构建的数据清洗方法控制初始数据质量,建立基础数据库,使用密度聚类（P-DBSCAN）、马尔科夫随机链等方法探索入境游客热点区域空间分布格局、流动空间特征。结果显示：① 北京市历史城区（2环之内区域）、中心城区（2环至5环之间区域）以及郊区（5环之外区域）的旅游热点区域（AOI）呈现出不同的空间特征,其中历史城区AOI呈现出与景区、休闲娱乐、餐饮购物等相关产业空间重叠的趋势,各热点区域边界模糊,复合连绵成片。中心城区AOI集聚与城市功能区密切相关,具有明确的城市功能取向。郊区AOI基本与旅游景点一致,没有向景区外部延伸;② 传统历史文化类AOI访问热度占有绝对优势,商业购物休闲AOI及现代城市功能AOI的影响力在逐渐增强;③ 强入境旅游流主要集中在历史城区内部AOI之间,以及中心城区的西北部与东部区域内部AOI之间,郊区AOI之间没有较强的旅游流,北京市入境旅游流整体呈现以历史城区为中心,放射性分布的框架;④ 各区域AOI之间均有较次一级旅游流联系,北京市入境旅游流形成了初步的网络结构。 相似文献
20.
The successful bid for the 2022 Winter Olympics has provided a new opportunity for the popularization of ice-snow sports and making improvements in the efficiency of ice-snow tourism in China. Taking Zhangjiakou City in Hebei Province as the research object and using questionnaire analysis and the structural equation model (SEM), this paper examined several hypotheses of the relationship between tourist experiential value and tourist loyalty in the context of ice-snow tourism, and a mediation analysis was conducted to explore the moderating role of travel companions. The results show that: (1) The functional value, emotional value and social value have significant positive effects on tourist loyalty; (2) Tourist satisfaction is a partial mediator between functional value, emotional value, social value and tourist loyalty, and a full mediator between cognitive value and tourist loyalty; and (3) Travel companions play a significant moderating role in the influence of emotional value on tourist loyalty. Based on these findings, several suggestions are put forward for the high-quality development of ice-snow tourism in China, including developing ice-snow family tourism products, building an ice-snow brand with winter Olympics characteristics, constructing the ice-snow industrial system, and cultivating ice-snow culture. 相似文献