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AI \u2013 or artificial intelligence \u2013 is often used as a way to summarize data and improve writing. But AI tools also represent a powerful and efficient way to analyze large amounts of text to search for patterns. In addition, AI tools can assist with developing research products that can be shared widely.<\/p>\n
It\u2019s with that in mind that\u00a0we<\/a>, as researchers in\u00a0social science<\/a>, developed a new\u00a0database of AI tools for the field<\/a>. In the database, we compiled information about each tool and documented whether it was useful for literature reviews, data collection and analyses, or research dissemination. We also provided information on the costs, logins and plug-in extensions available for each tool.<\/p>\n When asked about their perceptions of AI, many social scientists express caution or apprehension. In a sample of faculty and students from over 600 institutions, only\u00a022% of university faculty reported that they regularly used AI tools<\/a>.<\/p>\n From combing through lengthy transcripts or text-based data to writing literature reviews and sharing results, we believe AI can help social science researchers \u2013 such as those in psychology, sociology and communication \u2013 as well as others get the most out of their data and present it to a wider audience.<\/p>\n Qualitative research often involves poring over transcripts or written language to identify themes and patterns. While this kind of research is powerful, it is also labor-intensive. The\u00a0power of AI platforms to sift through large datasets<\/a>\u00a0not only saves researchers time, but it can also help them analyze data that couldn\u2019t have been analyzed previously because of the size of the dataset.<\/p>\n Specifically, AI can assist social scientists by\u00a0identifying potential themes<\/a>\u00a0or common topics in large, text-based data that scientists can interrogate using qualitative research methods. For example, AI can analyze 15 million social media posts to identify themes in how people coped with COVID-19. These themes can then give researchers insight into larger trends in the data, allowing us to refine criteria for a more in-depth, qualitative analysis.<\/p>\n AI tools can also be used to adapt language and scientists\u2019 word choice in research designs. In particular, AI can reduce bias\u00a0by improving the wording of questions<\/a>\u00a0in surveys or\u00a0refining keywords<\/a>\u00a0used in social media data collection.<\/p>\n Another key task in research is to scan the field for previous work to identify gaps in knowledge. AI applications are built on\u00a0systems that can synthesize text<\/a>. This makes literature reviews \u2013 the section of a research paper that summarizes other research on the same topic \u2013 and writing processes more efficient.<\/p>\n Research shows that human feedback to AI, such as providing examples of simple logic, can significantly improve the tools\u2019\u00a0ability to perform complex reasoning<\/a>. With this in mind, we can continually revise our instructions to AI and refine its ability to pull relevant literature.<\/p>\n However, social scientists must be wary of fake sources \u2013 a\u00a0big concern with generative AI<\/a>. It is essential to verify any sources AI tools provide to ensure they come from peer-reviewed journals.<\/p>\n AI tools can quickly summarize research findings in a reader-friendly way by assisting with writing blogs, creating infographics and producing presentation slides and even images.<\/p>\n Our database contains AI tools that can also help scientists present their findings on social media. One tool worth highlighting is\u00a0BlogTweet<\/a>. This free AI tool allows users to copy and paste text from an article like this one to generate tweet threads and start conversations.<\/p>\n Two-thirds of the tools in the database cost money. While our primary objective was to identify the most useful tools for social scientists, we also sought to identify open-source tools and curated a list of 85 free tools that can support literature reviews, writing, data collection, analysis and visualization efforts.<\/p>\nAnalyze text using AI<\/strong><\/h4>\n
Identify gaps in knowledge<\/strong><\/h4>\n
Share research findings<\/strong><\/h4>\n
Be aware of the cost of AI tools<\/strong><\/h4>\n