## 2 Backgrounds
### Using Chatbots in Qualitative Research  
AI has been applied in qualitative research since the 1980s, with early experiments focusing on developing expert systems that could understand natural language and was often used in professional settings like medical diagnostics to support or replace complex decision-making processes [34]. AI may have the power to disrupt the coding of data segments as a dominant paradigm for qualitative data analysis [35]. Although various AI-based tools can be used for qualitative data analysis, subscription fees are frequently required to utilize them entirely, making them unavailable to institutions and researchers with insufficient funding [24]. ChatGPT initially emerged as a language model. However, features like text shortening, interpretation, and detailed expression make it valuable for qualitative data analysis [36]. Using ChatGPT to analyse large quantities of qualitative data can significantly advance social studies and make it easier to incorporate AI-powered tools into standard social science research procedures [23]. ChatGPT is being investigated in various aspects and types of qualitative research, from transcription cleaning to theme generation through thematic analysis [24]. ChatGPT can accelerate the study of qualitative datasets, increase flexibility in comprehending and producing sociological knowledge, group codes into clusters, and help find patterns or connections [34]. ChatGPT is seen by qualitative researchers as a useful tool for thematic analysis, improving coding effectiveness, supporting preliminary data exploration, providing detailed quantitative insights, and supporting understanding by non-native speakers and non-experts [37]. Compared to conventional NLP techniques, which frequently call for in-depth programming expertise and complex coding processes, ChatGPT offers a strong substitute. Research outputs may be more effective and of higher quality because ChatGPT's user-friendly, conversational interface streamlines the analytical process [38]. Thematic analysis, a qualitative research method for identifying and interpreting patterns in data, is one application that stands to benefit from tools like ChatGPT [24]. ChatGPT can improve current procedures, collect qualitative data through informal surveys, analyze and extract characteristics from massive volumes of unstructured data, provide valuable market intelligence, and save researchers time and effort by being able to recognize context and provide meaningful information [39]. A more recent study [38] examined ChatGPT's ability to produce descriptive and thematically relevant codes, identify emerging patterns within a complex dataset, and conduct initial coding. This investigation demonstrated the model's proficiency at navigating large volumes of textual data and offered a detailed perspective on thematic evolution across documents. When using ChatGPT for the qualitative analysis in systematic literature reviews, the tool can provide an overall 88% accuracy in article discarding and classification, where the results are also very close to the results given by experts [40]. Using ChatGPT in qualitative research provides many advantages, including increased productivity and time savings, enhanced data exploration and accuracy, reduction of bias, consistency and inter-rater reliability, generation of new insights, iterative and collaborative analysis, ability to identify patterns and trends in social data, facilitated natural language interaction with research participants, aided accurate behavior prediction [23]. By automating the coding and categorization process, researchers can concentrate on other crucial facets of their work [23]. However, it should be noted that when the coding is automated, the researcher is no longer as familiar with the input data that make up the concept, which can introduce the danger of oversimplification.