Twitter and Academic Geography through the Lens of #AAG2018

Twitter has emerged as a global social network of active users who share conversations with one another in an online setting. Academics are one community that has increasingly taken to Twitter as a means of connecting with other scholars, sharing research, and obtaining meaningful feedback. Tweeting has become especially popular during academic conferences where conference attendees use Twitter hashtags to filter conference conversations into a separate dialogue. For geographers, the Annual Meeting of the American Association of Geographers (AAG) represents one such occasion to use Twitter to discuss contemporary developments in geographic research. In this article, we provide an overview of Twitter as well as the ways in which the academic community uses the platform. Following this, we discuss the tweets sent using the hashtag for the 2018 AAG Annual Meeting, #AAG2018. To analyze these tweets, we collected all tweets with this hashtag for a period of four weeks and examined the content using word clouds and sentiment analysis to explore general feelings and trends associated with geography and the AAG Annual Meeting. We conclude with suggestions for future research avenues that could use Twitter data to gauge the pulse of the geographic discipline. Key Words: academic conferences, American Association of Geographers, geography, sentiment analysis, Twitter.     

Discovery of local topics by using latent spatio-temporal relationships in geo-social media

ABSTRACT

Social networks have played a crucial role as information channels for people to understanding their daily lives beyond merely being communication tools. In particular, coupling social networks with geographic location has boosted the worth of social media to not only enable comprehension of the effects of natural phenomena such as global warming and disasters, but also the social patterns of human societies. However, the high rate of social data generation and the large amounts of noisy data makes it difficult to directly apply social media to decision-making processes. This article proposes a new system of analyzing the spatio-temporal patterns of social phenomena in real time and the discovery of local topics based on their latent spatio-temporal relationships. We will first describe a model that represents the local patterns of populations of geo-tagged social media. We will then define a local topic whose keywords share a region in space and time and present a system implementation based on existing open source technologies. We evaluated the model of local topics with several ways of visualization in experiments and demonstrated a certain social pattern from a dataset of daily Twitter streams. The results obtained from experiments revealed certain keywords had a strong spatio-temporal proximity even though they did not occur in the same message.     

Gender,Place, and Social Contacts: Understanding Awareness of Vulnerability to Terrorism

Abstract

Creating resiliency, accomplished in part by individuals preparing for disaster, is the primary strategy outside of law enforcement for responding to the threat of urban terrorism. Individuals prepare when they perceive a need to do so, yet little is known about what shapes a person's awareness of vulnerability to terrorism. Because evidence indicates that social contacts act as conduits of information and affect perception of risk to natural hazards, it is possible that such contacts also affect terrorism vulnerability awareness. Because social contacts are also known to be systematically segmented by gender and location, we hypothesized that conversations about terrorism vary by gender and place, specifically the home and work place. Drawing on data from 93 interviews with householders in Boston, the study demonstrates that: (1) family networks generated discussions of home preparedness, whereas workplace networks engaged a wider variety of topics; (2) women discussed terrorism more frequently and in greater depth than did men; and (3) women heard more preparedness messages for the home than did men, whereas men undertook preparedness activities external to the home. The findings bridge geography and terrorism studies by theorizing emplaced and subjective human experiences that prompt conversations about terrorism. These conversations, in turn, help urban emergency managers and risk-hazards geographers promote rational dialogue and action vis-à-vis terrorism. Hazards researchers have shown that the more people discuss terrorism, the less they seek extreme and unwarranted responses.     

Exploratory Spatiotemporal Analysis in Risk Communication during the MERS Outbreak in South Korea

The 2015 Middle East respiratory syndrome (MERS) outbreak in South Korea gave rise to chaos caused by psychological anxiety, and it has been assumed that people shared rumors about hospital lists through social media. Sharing rumors is a common form of public perception and risk communication among individuals during an outbreak. Social media analysis offers an important window into the spatiotemporal patterns of public perception and risk communication about disease outbreaks. Such processes of socially mediated risk communication are a process of meme diffusion. This article aims to investigate the role of social media meme diffusion and its spatiotemporal patterns in public perception and risk communication. To do so, we applied analytical methods including the daily number of tweets for metropolitan cities and geovisualization with the weighted mean centers. The spatiotemporal patterns shown by Twitter users' interests in specific places, triggered by real space events, demonstrate the spatial interactions among places in public perception and risk communication. Public perception and risk communication about places are relevant to both social networks and spatial proximity to where Twitter users live and are interpreted in reference to both Zipf's law and Tobler's law.     

广州市零售商业中心的居民消费时空行为及其机制

居民消费行为的空间选择及其影响因素是地理学的重点关注领域,已有研究对行为中时间选择、时空关系及内在机制的研究相对缺乏。为揭示居民消费时空行为形成的影响因素以及各因素内在相互作用机制,基于2016年广州城市居民消费行为调查数据,分析消费者到大型商业中心内消费的时空特征,构建结构方程模型,探讨消费时空行为影响因素和作用机制。研究表明：居民在商业中心的消费行为存在明显的时空差异。在影响路径方面,消费者社会经济属性通过影响消费偏好导致消费时空行为的差异,商业空间属性既可以直接影响消费时空行为,也可以通过影响消费偏好而间接对其施加影响,消费偏好既可以直接影响消费时空行为,又是消费者社会经济属性和商业空间属性影响消费时空行为的中间变量。在显著性因素方面,年龄、家庭结构、在广州居住时间、就业状况、家庭月收入等消费者社会经济属性变量会显著影响消费时空行为,各个商业空间属性变量都在不同程度上影响消费行为在时间和空间上的差异,仅有出行交通方式、出行花费时间2个消费偏好变量会显著影响消费者消费时空间行为。本文结论可以加深对商业中心内消费时空行为影响因素及其作用机制的理解,并为商业网点规划调整、商业中心转型升级提供建议。     

地理、网络与信任:金融危机背景下的生产网络演化

网络演化是演化经济地理学研究的重要内容和新近热点之一。在当前的理论探讨中主要强调路径依赖和惯例对网络演化的强化作用,对于信任这个关键要素缺乏深入探讨。本文通过深度访谈和问卷调查相结合的方法,对比金融危机前后广东省纺织服装行业生产网络的空间结构,揭示信任与生产网络演化之间的互动机制。研究发现:信任是维系生产网络稳定性的基本要素之一,信任的强弱程度主要受合作类型(市场关系)、地理接近(空间关系)和社会文化接近根植性(社会关系)等因素影响。金融危机作为一种负面外部冲击,重构了广东省服装行业的生产网络。在这个过程中,较强信任关系的网络连结(潮汕地区)得以保留,并在危机过后进一步强化;而部分较弱信任关系的网络连结(珠三角地区)发生断裂,且在经济回暖之后被潮汕地区的网络所取代。     

Geographical investigation of the network world: Basic principles and promising directions

Some specific characteristics typical of the emerging network society are considered by the author in the context of achievements of geography as a science. New directions and topics for investigations related to (i) the network business, (ii) the existing social and political networks are formulated. Analysis of the available experience bound up with geographical investigations of social-economic networks is given. The starting principles of a new (network) paradigm of social geography are outlined. Some promising directions of geographical investigations related to the information networks are defined and described.     

Spatial crime distribution and prediction for sporting events using social media

ABSTRACT

Sporting events attract high volumes of people, which in turn leads to increased use of social media. In addition, research shows that sporting events may trigger violent behavior that can lead to crime. This study analyses the spatial relationships between crime occurrences, demographic, socio-economic and environmental variables, together with geo-located Twitter messages and their ‘violent’ subsets. The analysis compares basketball and hockey game days and non-game days. Moreover, this research aims to analyze crime prediction models using historical crime data as a basis and then introducing tweets and additional variables in their role as covariates of crime. First, this study investigates the spatial distribution of and correlation between crime and tweets during the same temporal periods. Feature selection models are applied in order to identify the best explanatory variables. Then, we apply localized kernel density estimation model for crime prediction during basketball and hockey games, and on non-game days. Findings from this study show that Twitter data, and a subset of violent tweets, are useful in building prediction models for the seven investigated crime types for home and away sporting events, and non-game days, with different levels of improvement.     

基于社交媒体签到数据的城市居民暴雨洪涝响应时空分析

暴雨洪涝等小型地域性气候灾害给城市韧性带来挑战。以南京暴雨洪涝为例,通过挖掘新浪微博签到数据,构建公众感知指数和公众情绪指数,分析居民对暴雨洪涝响应的时空格局。在时间维度上,居民对暴雨洪涝的响应主要集中在暴雨洪涝期,并随灾害的严重程度而变化;在暴雨洪涝期内,居民在社交媒体上对暴雨洪涝的响应集中在早、晚高峰。在空间维度上,居民对暴雨洪涝的响应集中在主城区和3个新市区;重要交通基础枢纽地区和低海拔、经历快速城市化的新市区的居民对暴雨洪涝担忧程度更高。时空分析表明,暴雨洪涝对居民的交通出行影响最明显。基于时空间分析,最后从硬件和软件设施上为提升暴雨洪涝的城市韧性提供相关政策建议。     

西方乡村性研究进展

在梳理20世纪60年代以来乡村性研究的社会、学术背景的基础上,聚焦于乡村性的社会建构流派及其对中国乡村转型与乡村地理研究的启示。社会建构流派将乡村性看作是社会、文化建构的过程与产物而非先存的事实,重点关注乡村转型过程中的权力关系与差异性。由描述性流派、乡土流派向社会建构流派的过渡可以看作是从关注乡村性物质层面转向想象层面,由追求乡村性的本体、核心机制向探索乡村性的认识论问题,也就是从追求“乡村性是什么”到研究“不同社会群体如何认识乡村性”“不同社会群体多样化的乡村性话语和体验”。而目前的中国乡村性研究主要关注乡村性指标及其模型建构,相关研究对于各级政府全面地了解现存的乡村问题并合理地制定乡村发展、复兴政策规划具有重要的实践意义。在西方乡村研究中,乡村性指标由于暗含线性发展观、无法解读乡村变迁的机制和过程而饱受批判。在中国乡村急剧变迁的今天,现代化乡村发展话语占据着主导地位,而在这一过程中不公平的权力关系和霸权话语对部分农村、农民的边缘化基本没有提及。在这种社会与学术背景下,乡村性社会建构流派对于解构乡村性主导话语、揭示乡村变迁过程中的权力关系及不同社会群体间利益冲突与协商具有重要意义。     

西方尺度研究进展：概念化框架、实践路径及启示

通过梳理西方尺度研究的内涵和主要内容,发现尺度主要包含尺度本体论、尺度隐喻和尺度实践3个主要要素。尺度的本体论认为尺度是静态的等级化的物质实体,尺度的隐喻体现在尺度可通过话语进行多样化的解构和表达,尺度实践表示尺度通过不同行动者间的互动进行社会建构以实现尺度的再创造。尺度的3个要素之间既有统一性又有对立性：在统一性上,尺度本体论为尺度隐喻与尺度实践的实现创造了前提,尺度隐喻及尺度实践发展了尺度本体论;在对立性上,尺度本体论是实在论立场,尺度隐喻和尺度实践是建构论的产物。西方尺度研究主要经历了2个典型的阶段：将尺度物化为固定的空间实体;不同行动主体运用尺度进行社会实践或话语表达。这启示中国化的尺度研究需要将两者结合起来,既要承认物质空间实体的作用,也要接受行动者的能动性,将尺度看作是人、物相互作用的关系网络。文章展示了尺度概念化框架并实现了尺度的应用路径归纳,具体体现在尺度化、尺度解构及尺度政治3个方面。同时提出将资源配置效果纳入到尺度实践的分析要素之中以实现尺度的政治经济,这不仅扩充了尺度的理论内涵,还增加了尺度的实践应用效果和范围。     

An Approach to Field Experience in Eighth Grade Geography

Abstract

Man, the social animal, has organized his cities for particular social objectives. His urban social communications take place within a spatially and socially restrictive network of interpersonal information contact. Viewed in this sense, cities exist to facilitate the social communications or interactions of their population. At the same time, however, diverse social goals and group frictions create barriers to smooth flows of information among urban dwellers. This paper introduces the theme of urban social interaction, outlines the structure of social ties in cities, and surveys two major urban problems relating explicitly to social interaction in the city. The approach here is to bring geographical concepts and knowledge to bear on problems of social interaction in urban space. It is hoped that greater insight by teachers and students into the social problems of cities is achieved by an improved understanding of the geography of social communications.     

从技术中心主义到人本主义：智慧城市研究进展与展望

随着5G网络、物联网、云计算、大数据分析、地理信息系统等新技术的兴起,探索更具包容性和创新潜力的参与式治理,引导高效的技术研发与运用,实现城市“以地方现实为基础、以社会需求为导向”的智慧化转型,已成为国内外城市地理学的重要与前沿议题。人本主义视角下的智慧城市研究,为地理学者介入这一领域提供了理论工具。不同于技术中心主义将智慧城市视作由数字技术构成的物理空间集合,人本主义强调特定情境下的技术、社会(人文治理)与空间的互动。该视角呼吁对多方行动者参与技术研发、基础设施建设与治理决策的合作互动开展微观研究,以揭示智慧城市的共建过程与地方性驱动机制。论文梳理了国内外人本主义研究的最新进展,认为该视角下的研究仍然沿袭“技术中心”或采用与之对立的“知识中心”立场,而缺少技术—社会互动的视角来理解城市智慧化转型。论文提出未来值得深入探讨的议题,即技术与社会(治理)的共生性、围绕技术研发的社会关系互动复杂性、技术研发与关系互动的语境化分析。探讨以上议题有助于理解智慧城市如何作为一个复杂地域系统,在人与技术的持续互动中发生转型,也可为未来中国相关研究提供理论借鉴。     

Finding spatial outliers in collective mobility patterns coupled with social ties

ABSTRACT

Currently the increase in the variety and volume of data sources is demanding new data analytical workflows for exploring them concurrently, especially if the goal is to detect spatial outliers. In this paper, we propose a data analytical workflow for exploring Call Detail Records in conjunction with geotagged tweets. The aim was to investigate how massive data point observations can be analyzed to detect spatial outliers in collective mobility patterns that are coupled with social ties. This workflow consists of analytical tasks that are developed based on the a-priori assumption of two isometric spaces where Natural Language Processing techniques are used to find spatial clusters from geotagged tweets in a Social Space which are later used to aggregate the Call Detail Records generated by antennas located in the Mobility Space. The dynamic weighted centroids that are given by the mean location of the number of calls per hour of all antennas that belong to a particular cluster are used to compute Standard Deviation Ellipses. The longer the period of time a weighted centroid stays outside of the 99.7% probability region of an ellipse, the highest the likelihood that they are spatial outliers. The workflow was implemented for the city of Dakar in Senegal. The results indicate that the further the hourly weighted centroids are skewed from the normal mean of an ellipse, the stronger the influence of a cluster is in finding spatial outliers. Furthermore, the longer the period of time the outliers stays outside of the 99.7% probability region of an ellipse, the highest the likelihood that the outliers are genuine and can be associated to extraordinary events such as natural disasters and national holidays.     

接触型与非接触型犯罪时空稳定性对比及其联合防控——以盗窃和电信网络诈骗为例

近年来,以盗窃为代表的接触型犯罪和以电信网络诈骗为代表的非接触型犯罪均呈多发态势,严重影响社会治安稳定。已有研究对不同类型犯罪分布模式的时空稳定性关注仍不够,且未能提出不同类型犯罪的空间联合防控策略。本文以ZG市HT区为例,以社区为分析单元,运用核密度估计、时空跃迁测度法等方法,对比分析2017年盗窃犯罪和电信网络诈骗犯罪的时空分布特征及其空间分布模式的月度稳定性,并从犯罪防控角度改进时空跃迁测度法,结合二阶聚类法识别两类犯罪联合防控空间类型。研究发现：① 两类犯罪时空稳定性差异大,盗窃犯罪的空间分布模式稳定,月度变化小;而电信网络诈骗犯罪空间稳定性整体波动起伏大,月度变化较大;② 识别出两类犯罪的四种联合防控空间类型,分别是“两类犯罪无需防控社区”“两类犯罪邻域防控社区”“盗窃犯罪热点防控、电信网络诈骗犯罪无需防控社区”“盗窃犯罪连片防控、电信网络诈骗综合防控社区”。该研究有助于了解接触型犯罪和非接触型犯罪时空特征的共性和差异性,给警务联合防控提供决策支持。     

社会建构主义视角下的边界——研究综述与启示

边界是人文地理学研究中的一个关键概念。边界代表着一种空间秩序和空间关系,是解读边境地区社会与文化关系形成过程的一个关键维度。由于边界所界定的空间秩序与国家认同的建构、边境地区的经济社会发展、边民的身份认同等问题息息相关,因此学界对边界的社会功能与文化意义给予了持续关注。近年来,学者们逐渐从社会建构的视角重新诠释边界。边界不是地图上僵化的线,它所界定的空间关系与空间秩序,以及所承载的社会文化意义亦非固定不变的,而是国家与草根群体通过一定的社会与空间实践不断再生产与再建构。国家通过边界的营造刻写意识形态与国家认同,而普通社会群体对边界亦有着复杂的响应、调适与抵抗。在国际形势日趋复杂和变化的大环境中,边界凸显了新的意义和功能,重新认识边界如何打破旧的空间秩序并划定新的秩序,是人文地理学研究中值得关注的问题。本文从边界的内涵、边界的社会文化意义和跨边界实践3个方面出发,阐释建构主义下的边界在理论和实践层面的意义,并挖掘边界研究对国内研究的借鉴与启示。     

How to Earn the Status of Honest Broker? Scientists’ Roles Facilitating the Political Water Supply Decision-Making Process

“Honest broker” refers to scientists facilitating complex political decisions from a neutral position, aiming to expand the scope of choice available instead of advocating a certain policy. This article reflects on the experiences of three scientists acting as honest brokers while carrying out a multicriteria evaluation to help politicians choose the water supply option for the city of Oulu, Finland. The process was considered successful and many politicians said that they have never before been that well informed when making a decision. The case primarily shows that besides the common knowledge brokerage roles targeting knowledge exchange, the honest brokerage approach relates more to managing social relationships and balancing political games and rapidly evolving discussions. Trustful relationships increased the perceived credibility of the brokers and ensured two-way communication. On the other hand, the brokers faced ethical dilemmas and difficulties of staying impartial while finding out confidential information related to political strategies.     

Deep spatio-temporal residual neural networks for road-network-based data modeling

Recently, researchers have introduced deep learning methods such as convolutional neural networks (CNN) to model spatio-temporal data and achieved better results than those with conventional methods. However, these CNN-based models employ a grid map to represent spatial data, which is unsuitable for road-network-based data. To address this problem, we propose a deep spatio-temporal residual neural network for road-network-based data modeling (DSTR-RNet). The proposed model constructs locally-connected neural network layers (LCNR) to model road network topology and integrates residual learning to model the spatio-temporal dependency. We test the DSTR-RNet by predicting the traffic flow of Didi cab service, in an 8-km² region with 2,616 road segments in Chengdu, China. The results demonstrate that the DSTR-RNet maintains the spatial precision and topology of the road network as well as improves the prediction accuracy. We discuss the prediction errors and compare the prediction results to those of grid-based CNN models. We also explore the sensitivity of the model to its parameters; this will aid the application of this model to network-based data modeling.     

津巴布韦对中国国家形象的动态地理想象——基于批判地缘政治理论的分析

当前世界正在经历百年未有之大变局,中国如何积极构建其国家形象成为一个迫切需要回答的综合问题。研究援引批判地缘政治作为理论工具,以在津巴布韦的调查作为经验材料,探讨了津巴布韦不同主体对中国国家形象的动态地理想象及其机制。研究发现,津巴布韦对中国国家形象的地理想象不再受到以其国家宣传话语主导的基于殖民历史和独立战争的历史叙事所支配。相反,在其快车道土地改革运动、中国“走出去”战略及其与非洲日益紧密的联系,以及以“特朗普主义”为代表的全球地缘政治湍流不断等时代背景下,津巴布韦内外部社会关系产生了剧烈变化,不同主体之间（包括国家、政府、政党、协会、企业和个体等）的关系开始变得复杂,津巴布韦社会对中国国家形象的认知因此不再受到历史叙事的单方面影响,也受到流动的中国企业、移民及其在地实践,以及津巴布韦内外部社会关系变化与这种实践之间的互动的影响,从而对中国国家形象进行了不断解构和重构。研究拓展了批判地缘政治理论对话语的理解,强化了该理论与现实问题产生互动的潜力。从应用价值来看,研究讨论了它塑路径对中国国家形象营建的逻辑,对于全球转型背景下如何打造中国国家形象具有一定参考价值。     

洋能否为中用?西方政治地理与地缘政治发展的借鉴与反思

以西方为主的国外政治地理和地缘政治学说为中国政治地理和地缘政治的发展提供了很好的参照和基础。因此,如何理性对待西方的政治地理学和地缘政治学的研究、如何正确处理中国政治地理学和地缘政治学中的本土化与国际化关系是关乎中国政治地理学和地缘政治学学科方向的重要议题。然而,目前中国政治地理学和地缘政治学的发展在这一问题上存在困惑乃至两难。一方面,过度依赖西方研究框架和理论为中国政治地理学和地缘政治学的学科建设带来了一定风险;另一方面,在对西方研究保持谨慎态度的同时不能走向封闭乃至仇外的极端,破除“唯西方论”的同时不能走进“中国特殊论”的陷阱。为此,国内高校和科研院所从事政治地理和地缘政治研究的青年学者自发于2019年举办了一次“政治地理与地缘政治理论前沿”青年论坛,集中探讨了对西方政治地理与地缘政治发展的借鉴与反思,取得了初步的共识。具体而言,西方政治地理学和地缘政治学研究议题的多尺度性、研究方法的多样性、研究氛围的批判精神、研究视野的国际化和研究规范的严谨性等方面值得中国借鉴;而历史视角缺失、知识生产不平衡、地图空间表达不足、话语分析过多、解决现实问题不足等方面存在局限,中国政治地理学和地缘政治学未来发展过程中应加以避免。希望本次讨论抛砖引玉,吸引更多学者共同推动中国政治地理学和地缘政治学的学科发展。