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  • Romance Studies  (3)
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  • 1
    Online Resource
    Online Resource
    A Smooth Curve as a Fractal under the Third Definition
    University of Toronto Press Inc. (UTPress) ; 2018
    In:  Cartographica: The International Journal for Geographic Information and Geovisualization Vol. 53, No. 3 ( 2018-09), p. 203-210
    Details
    In: Cartographica: The International Journal for Geographic Information and Geovisualization, University of Toronto Press Inc. (UTPress), Vol. 53, No. 3 ( 2018-09), p. 203-210
    Abstract: It is commonly believed in the literature that smooth curves, such as circles, are not fractal, and only non-smooth curves, such as coastlines, are fractal. However, this article demonstrates that a smooth curve can be fractal, under a new, relaxed, third definition of fractal – a set or pattern is fractal if the scaling of far more small things than large ones recurs at least twice. The scaling can be rephrased as a hierarchy, consisting of numerous smallest, a very few largest, and some in between the smallest and the largest. The logarithmic spiral, as a smooth curve, is apparently fractal because it bears the self-similarity property, or the scaling of far more small squares than large ones recurs multiple times, or the scaling of far more small bends than large ones recurs multiple times. A half-circle or half-ellipse and the UK coastline (before or after smooth processing) are fractal if the scaling of far more small bends than large ones recurs at least twice.
    Type of Medium: Online Resource
    ISSN: 0317-7173 , 1911-9925
    URL: Article
    DOI: 10.3138/cart.53.3.2017-0032
    Language: English
    Publisher: University of Toronto Press Inc. (UTPress)
    Publication Date: 2018
    SSG: 7,26
    SSG: 14,1
    Location Call Number Limitation Availability
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Spatial Distribution of City Tweets and Their Densities
    Wiley ; 2016
    In:  Geographical Analysis Vol. 48, No. 3 ( 2016-07), p. 337-351
    Details
    In: Geographical Analysis, Wiley, Vol. 48, No. 3 ( 2016-07), p. 337-351
    Abstract: Social media outlets such as Twitter constitute valuable data sources for understanding human activities in the virtual world from a geographic perspective. This article examines spatial distribution of tweets and densities within cities. The cities refer to natural cities that are automatically aggregated from a country's small street blocks, so called city blocks. We adopted street blocks (rather than census tracts) as the basic geographic units and topological center (rather than geometric center) to assess how tweets and densities vary from the center to the peripheral border. We found that, within a city from the center to the periphery, the tweets first increase and then decrease, while the densities decrease in general. These increases and decreases fluctuate dramatically, and differ significantly from those if census tracts are used as the basic geographic units. We also found that the decrease of densities from the center to the periphery is less significant, and even disappears, if an arbitrarily defined city border is adopted. These findings prove that natural cities and their topological centers are better than their counterparts (conventionally defined cities and city centers) for geographic research. Based on this study, we believe that tweet densities can be a good surrogate of population densities. If this belief is proved to be true, social media data could help solve the dispute surrounding exponential or power function of urban population density.
    Type of Medium: Online Resource
    ISSN: 0016-7363 , 1538-4632
    URL: Issue
    URL: Article
    DOI: 10.1111/gean.2016.48.issue-3
    DOI: 10.1111/gean.12096
    RVK:
    RA 2430
    Language: English
    Publisher: Wiley
    Publication Date: 2016
    detail.hit.zdb_id: 2074885-1
    SSG: 14
    Location Call Number Limitation Availability
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    Online Resource
  • 3
    Online Resource
    Online Resource
    A Socio‐Geographic Perspective on Human Activities in Social Media
    Wiley ; 2017
    In:  Geographical Analysis Vol. 49, No. 3 ( 2017-07), p. 328-342
    Details
    In: Geographical Analysis, Wiley, Vol. 49, No. 3 ( 2017-07), p. 328-342
    Abstract: Location‐based social media make it possible to understand social and geographic aspects of human activities. However, previous studies have mostly examined these two aspects separately without looking at how they are linked. The study aims to connect two aspects by investigating whether there is any correlation between social connections and users' check‐in locations from a socio‐geographic perspective. We constructed three types of networks: a people–people network, a location–location network, and a city–city network from former location‐based social media Brightkite and Gowalla in the U.S., based on users' check‐in locations and their friendships. We adopted some complexity science methods such as power‐law detection and head/tail breaks classification method for analysis and visualization. Head/tail breaks recursively partitions data into a few large things in the head and many small things in the tail. By analyzing check‐in locations, we found that users' check‐in patterns are heterogeneous at both the individual and collective levels. We also discovered that users' first or most frequent check‐in locations can be the representatives of users' spatial information. The constructed networks based on these locations are very heterogeneous, as indicated by the high ht‐index. Most importantly, the node degree of the networks correlates highly with the population at locations (mostly with R 2 being 0.7) or cities (above 0.9). This correlation indicates that the geographic distributions of the social media users relate highly to their online social connections.
    Type of Medium: Online Resource
    ISSN: 0016-7363 , 1538-4632
    URL: Issue
    URL: Article
    DOI: 10.1111/gean.2017.49.issue-3
    DOI: 10.1111/gean.12122
    RVK:
    RA 2430
    Language: English
    Publisher: Wiley
    Publication Date: 2017
    detail.hit.zdb_id: 2074885-1
    SSG: 14
    Location Call Number Limitation Availability
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    Online Resource
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