Content analysis is a flexible research method widely used in library and information science (LIS) studies with varying research goals. It is applied in qualitative, quantitative, and mixed research frameworks and employs a range of analytical techniques. The article defines content analysis as a systematic, rigorous approach to analyzing documents obtained or generated in research. It distinguishes between quantitative and qualitative content analysis, showing that both are used in LIS. The article describes the steps involved in content analysis, provides examples from LIS studies, and serves as a gateway to methodological resources. Content analysis has roots in mass communication studies and has evolved to include various aspects of text, such as syntactic, syntagmatic, and pragmatic elements. It involves specialized procedures that allow for replication, especially in quantitative analysis. Data for content analysis can include text, images, and other meaningful materials. Texts used in LIS studies vary, including responses to open questions, interviews, reference interviews, published articles, and web pages. Data are "chunked" into units for sampling, collection, and analysis. Sampling units, data collection units, and units of analysis may differ. In quantitative content analysis, the coding scheme is determined a priori, operationalizing concepts and categories. Coding schemes are tested for validity and reliability, with categories being exhaustive, mutually exclusive, and measured at the highest possible scale. Coding schemes may be developed by researchers or adapted from existing ones. Quantitative content analysis involves steps such as establishing hypotheses, identifying data, sampling, coding, and analyzing data using statistical methods. Qualitative content analysis is inductive, with researchers developing hypotheses through open questions and iterative analysis. It focuses on understanding context and emerging patterns, with researchers using memos to track interpretations and refine their analysis. Both quantitative and qualitative content analysis use software to facilitate coding, data manipulation, and analysis. The article concludes that content analysis is a versatile method applicable to various research contexts, serving both qualitative and quantitative purposes. It highlights the importance of systematic and rigorous approaches in content analysis, emphasizing the need for validity, reliability, and contextual understanding.Content analysis is a flexible research method widely used in library and information science (LIS) studies with varying research goals. It is applied in qualitative, quantitative, and mixed research frameworks and employs a range of analytical techniques. The article defines content analysis as a systematic, rigorous approach to analyzing documents obtained or generated in research. It distinguishes between quantitative and qualitative content analysis, showing that both are used in LIS. The article describes the steps involved in content analysis, provides examples from LIS studies, and serves as a gateway to methodological resources. Content analysis has roots in mass communication studies and has evolved to include various aspects of text, such as syntactic, syntagmatic, and pragmatic elements. It involves specialized procedures that allow for replication, especially in quantitative analysis. Data for content analysis can include text, images, and other meaningful materials. Texts used in LIS studies vary, including responses to open questions, interviews, reference interviews, published articles, and web pages. Data are "chunked" into units for sampling, collection, and analysis. Sampling units, data collection units, and units of analysis may differ. In quantitative content analysis, the coding scheme is determined a priori, operationalizing concepts and categories. Coding schemes are tested for validity and reliability, with categories being exhaustive, mutually exclusive, and measured at the highest possible scale. Coding schemes may be developed by researchers or adapted from existing ones. Quantitative content analysis involves steps such as establishing hypotheses, identifying data, sampling, coding, and analyzing data using statistical methods. Qualitative content analysis is inductive, with researchers developing hypotheses through open questions and iterative analysis. It focuses on understanding context and emerging patterns, with researchers using memos to track interpretations and refine their analysis. Both quantitative and qualitative content analysis use software to facilitate coding, data manipulation, and analysis. The article concludes that content analysis is a versatile method applicable to various research contexts, serving both qualitative and quantitative purposes. It highlights the importance of systematic and rigorous approaches in content analysis, emphasizing the need for validity, reliability, and contextual understanding.