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00:00:00 – 00:09:46
The video from the Turning Point channel provides a thorough guide on crafting a PhD synopsis using ChatGPT, an AI-based language model. It emphasizes the initial importance of writing a synopsis, which includes conducting a literature overview, identifying key citations, recognizing research gaps, and formulating research objectives. The presenter demonstrates using ChatGPT to gather current literature, identify influential authors and top-cited papers, and emphasizes utilizing databases like IEEE Explore and ACM Digital Library for the latest studies. By analyzing research challenges and gaps, such as data quality and scarcity, the video shows how to establish research objectives and methods, including developing privacy-preserving AI models for urban mobility and addressing algorithm bias. The video concludes by summarizing the professional tone needed for writing research synopses and encourages audience engagement for future content.
00:00:00
In this part of the video, the presenter from the channel Turning Point introduces a guide on how to write a PhD synopsis using ChatGPT, an AI-based language model. The importance of writing a synopsis in the initial phase of research is highlighted. The video covers topics such as conducting an overview of literature, identifying top citations, recognizing research gaps and challenges, and formulating objectives. The presenter then demonstrates how to access ChatGPT by logging in with a Google account and initiating a new chat. An example query is provided for a literature review on AI in transportation and urban planning, showing how to begin formulating research using the tool.
00:03:00
In this part of the video, the presenter demonstrates how to use an AI tool to gather current literature on a given research topic. Initially, the AI provides an overview with nine key points on various aspects such as smart cities, environmental impact, challenges, and future directions. Despite its database being updated only until September 2021, the AI gives a comprehensive overview useful for continuing research. Subsequently, the presenter inputs a new query to obtain the top 10 citations in AI for transportation and urban planning, revealing influential authors, journals, and conferences for further study. Lastly, another query is made to generate a list of top-cited papers in the field, despite the AI’s limited access to all research databases, helping to identify significant research papers.
00:06:00
In this part of the video, the speaker discusses how to identify and incorporate research challenges and gaps into a research synopsis. They emphasize the importance of reviewing relevant papers and learning from the latest studies through databases like IEEE Explore, ACM Digital Library, and Science Direct. The speaker then demonstrates how to use research gaps and challenges to establish a foundation for research objectives. They highlight the need to focus on data quality and quantity, data scarcity, and other relevant topics. Finally, the speaker shows how to derive research objectives and methods based on these identified challenges, providing specific examples such as developing privacy-preserving AI models for urban mobility.
00:09:00
In this part of the video, the speaker discusses the rationale and methods of data analysis and the second objective of mitigating algorithm bias while designing scalable AI solutions. The speaker notes that the language used is very professional, suitable for research theses or synopses, providing a complete framework for continuing research. The video concludes with an appeal for viewers to like, subscribe, and share the video, and to comment if more videos on similar topics are desired.