# Tourism Sentiment Chain Representation Model and Construction from Tourist Reviews
## 4 Results
### Attribute Extraction and Analysis of Tourist Attractions
#### 4.2.2 Attraction Entity Attribute Analysis  
(1) Thematic Features  
Following the extraction of textual entity features, an analysis was conducted on the distribution ratios of various types of opinion phrases present in the review texts for all tourist attractions under investigation, as illustrated in Figure 6. \"Environment and Landscape\", \"Services and Facilities\", and \"Leisure and Entertainment\" are the primary themes of interest for tourists. In contrast, \"Transportation and Travel\", \"Food and Shopping\", and \"Price and Consumption\" receive less attention.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Thematic Classification** & **Precision** & **Recall** & **F1-Score** & **Support** \\ \hline Transportation and Travel & 0.9134 & 0.9045 & 0.9089 & 618 \\ Environment and Landscape & 0.9250 & 0.9530 & 0.9388 & 5223 \\ Services and Facilities & 0.9044 & 0.8749 & 0.8894 & 2390 \\ Food and Shopping & 0.8971 & 0.8824 & 0.8897 & 425 \\ Price and Consumption & 0.9651 & 0.9651 & 0.9651 & 1779 \\ Crowd Flow and Density & 0.9355 & 0.9348 & 0.9352 & 1211 \\ History and Culture & 0.8346 & 0.7902 & 0.8118 & 696 \\ Family and Education & 0.9031 & 0.9417 & 0.9220 & 1029 \\ Animals and Plants & 0.8994 & 0.8824 & 0.8908 & 1216 \\ Leisure and Entertainment & 0.9183 & 0.9032 & 0.9107 & 3036 \\ \hline micro avg & & & 0.9184 & 17,629 \\ macro avg & 0.9096 & 0.9032 & 0.9062 & 17,629 \\ weighted avg & 0.9181 & 0.9184 & 0.9181 & 17,629 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Evaluation of viewpoint phrase thematic classification accuracy.  
After extracting thematic features of tourist attractions using Equation (4) from Section 3.1.2, the thematic distribution vectors of the top 9 attractions in Wuhan's popular attractions list were analyzed to demonstrate that the indicators align with the cognitive expectations. In each subplot, the sector azimuth encodes the ten thematic dimensions of the attraction, representing the multidimensional experiential quality perceived by visitors. The radial length quantifies the proportion of visitor attention (%) allocated to each theme, as shown in Figure 7. Both the Yellow Crane Tower and Qingchuan Pavilion demonstrate over 25% attention toward the \"History and Culture\" theme, with attention levels hovering around 10% across other dimensions--highlighting the \"History and Culture\" experience as their dominant appeal. Likewise, Happy Valley and Maya Beach Water Park emphasize \"Leisure and Entertainment\". Wuhan University, Haichang Polar Ocean World, and East Lake Ocean Paradise focus on \"Family and Education\" and \"Animals and Plants\". Wuhan University discusses \"History and Culture\" more than the other two, while East Lake Ocean Paradise is more noted for its \"Price and Consumption\"--Wuhan Garden Expo Park and Mulan Prairie show balanced performances across various themes without any dominant one. The construction and analysis of thematic distribution vectors yield results that are highly consistent with the actual functional positioning and tourist perceptions of attractions. Significant differences among attractions indicate that thematic distribution vectors effectively capture core thematic features and subtle variations.