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The use of social networks in online research is increasing. More and more studies are using these platforms to recruit participants. The conventional approach used in the past, based on classic research methods such as personal interviews, surveys, focus groups or content analysis has been replaced by automated tools that allow data to be rapidly collected without the need for human interaction. This paper presents an online interactive method for analyzing social media content through response trees (RTs). The RT was applied to 1) analyze public reactions on Twitter about a topic of interest; 2) gain insights into emotions expressed by various users during 1 month following a terrorist attack; and 3) understand how certain tweets affect people’s health behaviors. The RT analytical method shows that it is possible to collect and analyze data with a large number of users on social media. In addition, the method can be used to predict theories, create awareness among the public and provide insights on how people react to events. The RT is a more accurate tool for analyzing social media content compared to classical research methods such as surveys and interviews. This study provides a better understanding of what triggers people’s emotions in a specific situation, what influences their reactions and why some groups show similar reactions while others remain indifferent. The RT can also be used during “real time” situations where data is automatically collected from social media users without any human interference. The RT can help to identify which social media users are most influential based on their influence on the total number of tweets, attracting more people to react to news events. The study found that some types of information are perceived differently by different groups. People with higher education tend to be more desensitized toward death and suffering than those with lower education. Therefore, it is possible that increased education levels could lead to fewer people expressing their grief and sadness on social networks. These software tools give participants an opportunity to participate in an online survey without having any previous knowledge or qualifications for doing so. The users’ responses are recorded automatically and can be analyzed automatically by a researcher. There are several web-based applications that provide computer-aided tools for analyzing social media content, collecting consumer opinion or conducting surveys. Participants can report their opinions on a variety of topics using the application, including politics, arts and culture, popular culture, lifestyle and products. There are several web-based applications and tools used across all areas of social sciences to analyze Twitter data (anonymized and de-anonymized), such as: These software tools give researchers access to large amounts of users' data with the help of internet search engines. They allow researchers to find data regarding a specific topic, e.g., sentiment analysis, online reputation or key influencers. Anonymized and de-anonymized social media data is one of the main tools used in cultural heritage research. archaeologists, linguists and anthropologists use this type of data to analyze trends in cultural diffusion, memory and identity. However, the use of social media technology in cultural heritage research has been very limited until recent years because of the lack of automated tools that allow researchers to analyze large amounts of social media content quickly and easily. cfa1e77820
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