Speaker 1: When you enter a research field, there is so much literature you need to find, then I'm gonna share with you the different ways that you can find literature because it is a nightmare out there. There are more tools than ever and more methods than ever for finding literature and luckily AI is to the rescue because there are plenty of tools that you can utilize for different circumstances. The first way that you can look for literature is with questions. This is one of my favorite ways. I love that AI has allowed us to do semantic searching. So if you have a question that pops into your mind while you're sort of doing research, while you're searching the literature, you can go to these tools and just type in a question. I love it. So here we are. Why do academics feel sad? And then we can go have a look. It's searching for papers. It's looking for abstracts. It actually summarizes four abstracts for you and it gives you a final answer. So here we are. This is the top four paper summary and then it gives you loads and loads of stuff that you can start exploring the literature. So if a question pops into your mind, bing, just type it into semantic search and you'll be amazed at the sort of questions that you can find in the peer-reviewed literature being answered. I love it. And there are more ways that you can search the literature that are just as powerful. When I was a researcher, I actually started a lot of my projects with like these seed papers, with papers that gave you a hint that there was something interesting and exciting if only you were to explore a certain little area. So if you've got a seed paper given to you by your supervisor, by someone else in the lab, or you find one yourself, you can explore the literature and themes around that paper in these three tools. They're all different. They all kind of do a similar job, but they sort of excel in different things in different ways. The first one is litmaps. Here we can explore by seed maps, by discover and visualize. The one thing I love about this is that as soon as you put in a seed article, you get a map. You can explore this map in a load of different ways, and you can also just sort of like sort by different ways. So if I want to look by momentum, I can see that these are actually sort of like high momentum articles. So these are ones that are being cited a lot. So these ones should sort of like be on my to read list. Absolutely. Another thing that you can use is connected papers. Once you put a seed paper in, the one thing that I love about this is you've got prior works and derivative works. I use these a lot. Quite often I look for derivative works because that gives you more up-to-date information, and it allows you to quickly fill up your literature search. And yeah, I really like this. As you can see, it's much more recent papers, and it gives you by last author citations and references, so you can sort it however you want. And then Research Rabbit is another one. If you put in one selected paper, the one thing I love about this is that not only do you get a map, but you also get all these other ways that you can sort of like search, or references, or citations, or these authors. And so this is a really good way of just sort of like going out and snowballing, and we'll talk about that in a little bit. We'll snowball the amount of literature that we find. And yeah, suggested authors over here, you get a nice map. The one thing about Research Rabbit is it is really complicated when you first look at it, but by just sort of like playing with it for a little bit, you'll really see how powerful it is. So lit maps, connected papers, and Research Rabbit are brilliant. If you have papers that you want to explore around Brill. In any research field that you enter, there are typically famous and well-known authors that you should be following, and finding out what they're doing. Underneath those authors, they have PhD students, they have research assistants, they have so many other people that are producing data and papers around the themes in which they research. So if you find an author, just head over to their academic research portfolio page, and you'll be amazed at the papers that you can find. So I head over here. This is Dr. Christopher Gibson. He is one of my favorite people in the world, in academia. If you can, send him an email, and just say, do you know what? Dr. Andy Stapleton loves you. If you want to call him as well, give it a go, why not? He'll love it. So here's Dr. Christopher Gibson. You can see that he's got this lovely research portfolio, but if I go to Research Outputs, this is where all of his recent papers are collected together, and these are kept up to date. It's these research pages as well as group websites that are the most up-to-date, because people want to keep that up-to-date, because it's all part of their promotions. It's all part of doing better in academia. So this is where a lot of really up-to-date information can be found, as well as conference presentations that they've given, all that sort of stuff. So here we are. You can see that in 2023, we've already got these three papers. 2022 was a bumper year for Dr. Gibson, and overall, yeah, this is where you can find a lot of really good information. And if you also look at their PhD students, their master's students, and anyone else doing research in their research group, I would follow those researchers as well, because really, they're the people, the academic workhorses of the lab that are producing the data that you need. So look for authors, get a list of people that you should follow, and you'll almost certainly always get the most important information straight into your literature collection, your folder on your computer. All right, there's more ways, and this one is pretty interesting. When I was a researcher and a PhD student, the only ways you could find paper was going through dusty, horrible libraries to find papers. Pfft, pfft. But also, you could just type in keywords to Google, Google Scholar, and other kind of like literature search engines. But now, those still exist, but there's an even better way to find out what you should be searching for. So I head over to something like ChatGPT, and I just ask it for what keywords I should be searching for in a given field. So you can see up here, I've got, I am doing a literature search on organic photovoltaic devices. I'd like some keywords that will help me find papers in Google Scholar. And then, yeah, it gives me this blurb, but ultimately, it gives me this, 20 key terms that I can actually use in Google Scholar. And I went in and typed in charge transport OPVs, and you can see that I've got a load of really interesting stuff that maybe I wouldn't have searched for if I didn't know that keyword. I can go to since 2023, and you can see that already this year, there's been a load of papers. And this is a great way of just collecting all that information and getting it into a folder. And then, you have to spend time reading it later, summarizing, skimming things, because that's what academia's all about. But it's about just sort of like getting that big mass of papers, and then you sort of like work your way through them in bite-sized chunks over the course of a month or so. Yeah, information, information, yeah. Yeah, bite-sized information, yeah. The last method you should know about is the snowball method. This is messy, this takes a lot of time, but if you've got enough energy, and this is really good if you sort of like feel like you've hit a dead end in what you're reading, or you're feeling less inspired because everything's starting to sound the same, the snowball method is just a brilliant way to re-energize that literature search, and it all starts with one paper. So let's say you've got this paper here, and you're like, okay, yeah, this is fine. But this is where the snowball method really takes hold, is you start getting the papers indiscriminately. You go, okay, well, this is number 14, let's have a look at number 14. Okay, I want that, let's go have a look at that. So you go to polymer blends based on whatever that says. Novel approaches to polymer blends based on polymer nanoparticles. So you go there, let's go find it. There we are, it's right here. So let's go in and have a look at this, and then I want to know, this article is cited by, and then we just start opening tabs. This is what we do, it's indiscriminate, we do not care about what we're looking at really, but it's about filling up as many tabs as possible, snowballing it so that you're almost sort of like certain, just going to sort of like come across things that maybe you wouldn't have thought about looking at in the past. So once you've got sort of like, you know, a nice load of tabs up here, you want to just go through and you go, okay, advances in green solvent processable polymer solar cells. Well, that's interesting to me. I'll actually download that reference and put it into my reference manager and save the PDF somewhere. Okay, then there's this one, synthesis and application of green solvent dispersed organic semiconducting nanoparticles. Yeah, I definitely want that one. And you just keep doing this. And then once you get to this paper, you go, okay, well, let's have a look, let's just see who they reference. And then let's go and have a look at Google Scholar. And I just open up as many tabs as humanly possible. And I just sort of like just start going through them. So overall, it's just about snowballing, is about sort of like not trying to do that initial filter and just get as much information as possible, get it stored somewhere, open tabs, download the PDFs, and then just start reading and skimming. I like doing the snowball when I've just got a little bit of time and I can't be arsed reading, but I just know I need to get some literature to sort of like start that next process of understanding new ideas, new concepts in and around my field. So snowballing is something I did all the time when I was a PhD student. And it's something that I think you could benefit too. It's messy, it's manual, but that's the point. If you like this video, go check out this one where I talk about writing a literature review with AI. It's easier than ever to get loads of literature, synthesized and distilled down into a spite-sized kind of literature review to really empower your research direction. Go check it out, because there's a lot of value. So there we have it. There's everything you need to know about finding literature with AI. These different techniques and tools are going to help you get all of that information and synthesize it down so you know what's going on in your research field, where the gaps are, and where you should be heading. It's really powerful. Let me know in the comments what you would add and how you do it, because I love reading your expertise and it really helps inform these videos. Thank you so much. All right, then, there's more ways that you can engage with me. The first way is to sign up to my newsletter. Head over to andrewstepton.com.au forward slash newsletter. The link is in the description. And when you sign up, you'll get five emails over about two weeks, everything from the tools I've used, the podcast I've been on, and how to write the perfect abstract, and more. It's exclusive content available for free, so why wouldn't you sign up? Hmm? Why wouldn't you? And also, go check out academiainsider.com. That's my project where I've got e-books, I've got resource packs, I've got the blog, I've got the forum, and courses are coming soon, and everything is over there to make sure that academia works for you. All right, then, I'll see you in the next video.