ellynnhitran
commented
2 months ago Thanks Tuan for your feedback on our proposal. We appreciate your thoughtful suggestions for enhancing our project's novelty and effectiveness.
Addressing Feedback: - Novelty and Uniqueness: We agree that integrating sentiment data with additional contextual factors such as weather, events, or economic indicators could provide richer insights and elevate the project's novelty. We plan to explore potential data sources and integration methods that could complement our sentiment analysis.
- Approach and Technology: We acknowledge the importance of scalability and real-time capabilities, particularly with large datasets over extended periods. We will investigate the feasibility of integrating additional visualization libraries like Plotly to offer more interactive and dynamic features.
- Enhancements and Additional Features: Your suggestion to incorporate sentiment trend analysis over time is great. We aim to implement this feature to show how sentiments evolve during significant events or holidays, providing a temporal dimension to our analysis. Additionally, extending our sentiment categories to include specific emotions such as joy, sadness, and anger will allow for a more detailed understanding of regional sentiments.
- Questions and Clarifications: To address city name variations or misspellings in Reddit posts, we plan to implement a robust preprocessing step that includes mapping common misspellings to correct city names based on a predefined list. For biases in sentiment analysis, we will conduct periodic reviews of our model's performance across different topics and languages to ensure balanced representation and accuracy.
- Imagined Feature: The idea of comparing sentiments between cities or regions is intriguing. We envision implementing a feature that allows users to select multiple cities or regions for a comparative sentiment analysis, potentially uncovering cultural insights and regional differences in perceptions.
Looking forward, we will implement these improvements to achieve better project outcomes.
Feedback on Proposal:
Vu and Tran Tue Nhi, your proposal for a sentiment analysis visualization of Vietnamese cities using Reddit data is intriguing and well-structured. Here are some insights and suggestions for enhancing your project's novelty and effectiveness:
Novelty and Uniqueness: Your project's concept of mapping sentiment analysis onto Vietnamese cities through Reddit headlines is innovative. While sentiment analysis and geographic data visualization are not new, combining these techniques to analyze regional sentiments in Vietnam specifically adds a unique dimension. To further enhance novelty, consider exploring the integration of sentiment data with other contextual factors like weather, events, or economic indicators to provide richer insights.
Approach and Technology: The use of the Reddit API coupled with VADER sentiment analysis and visualization through R's choropleth maps is a solid approach. However, consider the scalability and real-time capabilities of your solution, especially with large datasets over extended periods. You might also explore integrating other visualization libraries like Plotly for more interactive and dynamic features.
Enhancements and Additional Features: To enrich your visualization, consider incorporating sentiment trend analysis over time, perhaps showing sentiment shifts during significant events or holidays. Additionally, providing sentiment breakdowns beyond positive, negative, or neutral (e.g., emotions like joy, sadness, anger) could offer deeper insights into regional sentiments.
Questions and Clarifications: It would be beneficial to clarify how you plan to handle city name variations or misspellings in Reddit posts to ensure accurate city-to-headline mapping. Additionally, how will you address potential biases in sentiment analysis towards specific topics or languages prevalent on Reddit?
Imagined Feature: A valuable addition could be sentiment comparison between cities or regions, highlighting differences in perception across Vietnam. For instance, a feature allowing users to contrast sentiments between northern and southern cities could yield interesting cultural insights.
Overall, your project proposal is comprehensive and well-conceived. By considering these suggestions, you can further elevate the uniqueness and functionality of your sentiment analysis visualization, offering actionable insights for diverse stakeholders. Good luck with your project implementation!