Shaping an alternative smart city discourse through Twitter: Amsterdam and the role of creative migrants

Monachesi, Paola

doi:10.1016/j.cities.2020.102664

Cited by 21 publications

(7 citation statements)

References 51 publications

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“…Researchers are able to use collected Twitter data to conduct studies in many different scientific domains, such as public health, law, computer science, etc. (Arthur and Williams, 2019; Colditz et al , 2018; Kim et al , 2020; Monachesi, 2020; Ren et al , 2019; Samoggia et al , 2020). Since the Twitter API prevents published tweets being accessed after seven days, an open source tool called Twint [1] was used since this enables unlimited access to any tweet ever posted and gathers tweets according to username or keyword.…”

Section: Methodsmentioning

confidence: 99%

Analyzing tourist data on Twitter: a case study in the province of Granada at Spain

Viñán-Ludeña

Campos

2021

JHTI

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PurposeThe main aim of this paper is to build an approach to analyze the tourist content posted on social media. The approach incorporates information extraction, cleaning, data processing, descriptive and content analysis and can be used on different social media platforms such as Instagram, Facebook, etc. This work proposes an approach to social media analytics in traveler-generated content (TGC), and the authors use Twitter to apply this study and examine data about the city and the province of Granada.Design/methodology/approachIn order to identify what people are talking and posting on social media about places, events, restaurants, hotels, etc. the authors propose the following approach for data collection, cleaning and data analysis. The authors first identify the main keywords for the place of study. A descriptive analysis is subsequently performed, and this includes post metrics with geo-tagged analysis and user metrics, retweets and likes, comments, videos, photos and followers. The text is then cleaned. Finally, content analysis is conducted, and this includes word frequency calculation, sentiment and emotion detection and word clouds. Topic modeling was also performed with latent Dirichlet association (LDA).FindingsThe authors used the framework to collect 262,859 tweets about Granada. The most important hashtags are #Alhambra and #SierraNevada, and the most prolific user is @AlhambraCultura. The approach uses a seasonal context, and the posted tweets are divided into two periods (spring–summer and autumn–winter). Word frequency was calculated and again Granada, Alhambra are the most frequent words in both periods in English and Spanish. The topic models show the subjects that are mentioned in both languages, and although there are certain small differences in terms of language and season, the Alhambra, Sierra Nevada and gastronomy stand out as the most important topics.Research limitations/implicationsExtremely difficult to identify sarcasm, posts may be ambiguous, users may use both Spanish and English words in their tweets and tweets may contain spelling mistakes, colloquialisms or even abbreviations. Multilingualism represents also an important limitation since it is not clear how tweets written in different languages should be processed. The size of the data set is also an important factor since the greater the amount of data, the better the results. One of the largest limitations is the small number of geo-tagged tweets as geo-tagging would provide information about the place where the tweet was posted and opinions of it.Originality/valueThis study proposes an interesting way to analyze social media data, bridging tourism and social media literature in the data analysis context and contributes to discover patterns and features of the tourism destination through social media. The approach used provides the prospective traveler with an overview of the most popular places and the major posters for a particular tourist destination. From a business perspective, it informs managers of the most influential users, and the information obtained can be extremely useful for managing their tourism products in that region.

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Section: Methodsmentioning

confidence: 99%

Analyzing tourist data on Twitter: a case study in the province of Granada at Spain

Viñán-Ludeña

Campos

2021

JHTI

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“…Word frequency statistics constitute the most basic and effective method. Most word frequency statistics rely on computational methods [60]. Kim et al [61] selected the High Line Park as a research case and conducted text mining on Twitter texts over one year.…”

Section: Natural Language Processing and Text Miningmentioning

confidence: 99%

Social Media Data in Urban Design and Landscape Research: A Comprehensive Literature Review

Yang

Liu

2022

Land

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Social media data have been widely used in natural sciences and social sciences in the past 5 years, benefiting from the rapid development of deep learning frameworks and Web 2.0. Its advantages have gradually emerged in urban design, urban planning, landscape architecture design, sustainable tourism, and other disciplines. This study aims to obtain an overview of social media data in urban design and landscape research through literature reviews and bibliometric visualization as a comprehensive review article. The dataset consists of 1220 articles and reviews works from SSCI, SCIE, and A&HCI, based on the Web of Science core collection, respectively. The research progress and main development directions of location-based social media, text mining, and image vision are introduced. Moreover, we introduce Citespace, a computer-network-based bibliometric visualization, and discuss the timeline trends, hot burst keywords, and research articles with high co-citation scores based on Citespace. The Citespace bibliometric visualization tool facilitates is used to outline future trends in research. The literature review shows that the deep learning framework has great research potential for text emotional analysis, image classification, object detection, image segmentation, and the expression classification of social media data. The intersection of text, images, and metadata provides attractive opportunities as well.

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“…Discourse analyses on bodies of Twitter data have been used in multiple urban and environmental planning contexts; for example, past research has identified alternative stories about the smart city as told by creative skilled migrants (Monachesi, 2020), assessed public engagement in the management of protected areas (Bhatt and Pickering, 2021), and analyzed the psychological benefits of urban green space use (Plunz et al, 2019). Additionally, recent literature has begun to use Twitter discourse analyses to ascertain how discourses in urban planning and natural resource management are constructed between planners and the public (Williamson and Ruming, 2017;Boyer et al, 2021).…”

Section: Analyzing Discourses About Urban Planning On Social Mediamentioning

confidence: 99%

Methods for Uncovering Discourses That Shape the Urban Imaginary in Helsinki's Smart City

Zaman

Hertweck

2022

Front. Sustain. Cities

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In modern urban environments the technologies that are basic to everyday life have become further embedded in that life. Smart cities are one example of the acceleration of technological change in order to engage with urban sustainability challenges, with Artificial Intelligence (AI) tools as one mode of engagement. However, the discourses through which cities engage with smart city growth and management can have long-term consequences for diverse knowledge held within the imaginaries of situated smart urbanism. As the city of Helsinki increasingly focuses on sustainable smart city initiatives, concurrent research suggests that smart urbanism is at a crossroads, where developers must decide how smart cities choose to engage with its residents' knowledge. This research sets out to ask, how are top-down smart city interventions communicated on Twitter (de)legitimizing diverse knowledge in situated smart urbanism? We draw from Foucaudian theory to identify which discourses are elevated, through statements posted on the social media platform Twitter. By answering this question, our goal in this paper is to examine how Foucault's methods can be used to highlight unseen assumptions about smart urbanism in Helsinki. Our objective is to identify overarching narratives and potential contested conceptualizations of smart urbanism in Helsinki. With our methods, we contribute a novel angle to surfacing power relations that are becoming evident in the development of AI-governed smart cities.

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Shaping an alternative smart city discourse through Twitter: Amsterdam and the role of creative migrants

Cited by 21 publications

References 51 publications

Analyzing tourist data on Twitter: a case study in the province of Granada at Spain

Analyzing tourist data on Twitter: a case study in the province of Granada at Spain

Social Media Data in Urban Design and Landscape Research: A Comprehensive Literature Review

Methods for Uncovering Discourses That Shape the Urban Imaginary in Helsinki's Smart City

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