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Journal of Chinese
            Architecture and Urbanism                                             Urban features of PRD in online image



                                                               4.2.2. High-frequency texts

                                                               The frequency of text words reflects the main spatial carrier
                                                               and media communication content in the presentation of
                                                               town images. By analyzing the top-ranked high-frequency
                                                               words in the texts associated with each town (Table 7), it
                                                               is evident that the primary terms are “valley” (18.52%),
                                                               “tourism” (12.35%), “countryside” (8.64%), and “urban
                                                               areas/communities” (3.70%). The remaining words appear
                                                               in <3% of the texts, indicating that public perception is
                                                               strongly shaped by topography, behavior, and regional
                                                               features. Among second-ranked high-frequency words,
                                                               “culture,” “park/tourism,” and “landscape” are dominant,
                                                               reflecting that the public’s impressions of small towns are
                                                               shaped by cultural communication and the visual image of
            Figure 4. Town scene components in rotated space   towns conveyed through nodes of public open space.
            Source: Graph by the authors.
                                                                 The content and value of text word frequencies reflect
                                                               public attention hotspots. By summing the frequency of
            living places, connectivity, and roadside landscapes, is   the top three words in the text for each town and dividing
            central to the image expression of these towns in the   the towns into five equal groups based on word frequency
            networked space.                                   values (Figure 6), it becomes clear that towns recognized as
              The locations of towns and their functional relationships   famous tourist destinations in traditional public perception
            with large-  and medium-sized cities significantly shape   exhibit markedly higher word frequencies than industrial
            their spatial scenes. The research statistically identifies the   towns.  Among  famous  tourist  towns,  Yuecheng  town  in
            image labels of townscapes and countryside landscapes   Zhaoqing City, home to the renowned Dragon Mother
            and categorizes them into three groups (Figure 5):  Ancestral Temple, has a word frequency value more than
            (i)  Urban–rural integration category: Found mainly   double that of other towns. Other notable towns include:
               in Guangzhou and Dongguan, these central towns   •   Lubao town in Foshan city, known for its hot springs
               exhibit  prominent natural characteristics,  alongside   resorts;
               diverse  urban  scenes,  such as  modern  urbanization   •   Shawan historical town in Guangzhou city, a nationally
               and local culture.                                 recognized historical and cultural town;
            (ii)  Rustic-dominated category: Towns in Huizhou,   •   Siqian town in  Jiangmen  city, branded as the
               Jiangmen,  and  Zhaoqing  are  characterized  by   “Thousand-Year Old Town, Hundred-Year Dragon
               pronounced agricultural and rustic scene features.  Boat;” and
            (iii) Town-dominated category: Towns in Zhuhai,    •   Xiaolan town in Zhongshan city, celebrated as the
               Zhongshan, and Foshan are primarily defined by     hometown of cultural and folk arts.
               townscapes featuring parks, squares, and urban    In  contrast,  industrial  towns  show  a  different  focus.
               landmarks.                                      Examples include:
                                                               •   Lecong town in Foshan city, a hub for traditional
              The high degree of urbanization and the clear functional   home furnishing;
            division in surrounding towns (Shen et al., 2023) contribute   •   Xinxu town in Huizhou city, aiming to establish an
            to the diversity of image labels in central towns. In medium-  industrial park with an output value exceeding 100
            urbanized areas, fewer central towns exist, but their image   billion RMB by leveraging its proximity to Shenzhen;
            scenes are more prominently related to urban characteristics.   and
            Conversely, in less urbanized areas, there are more central   •   Yangcun town in Huizhou city, featuring a provincial
            towns, with scene characteristics predominantly shaped by   industrial transfer park and the Bodong Industrial
            agriculture and countryside features.                 Park agglomeration area.
              Overall, most town scenes align with public perceptions.   These findings underscore the dual role of central towns
            Identifying towns that deviate from the dominant regional   in the PRD. While they serve as leisure and suburban tourism
            characteristics can further uncover unique development   destinations for residents of large-  and medium-sized
            potential or heritage resources.                   cities, they also play a pivotal role in facilitating industrial


            Volume 7 Issue 2 (2025)                         9                        https://doi.org/10.36922/jcau.5733
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