There are several free tools available to support researchers in gaining a broad overview of the research landscape. These tools typically fall into two categories: literature mapping tools and AI-powered research tools.
Literature mapping tools help researchers explore the wider relationships between articles. They can generate visual maps of citation networks using one or more ‘seed’ papers, or even just a search term, making them particularly useful at the outset of an evidence synthesis. These maps can help identify clusters of related work, trace the development of ideas over time, and ensure that key or seminal works have not been overlooked.
AI-powered research tools offer a complementary way to engage with the literature. These tools use advanced language models to assist with tasks such as refining research questions, identifying relevant studies, summarising key findings, and extracting structured data from academic texts.
Some of these tools and their key features are outlined below.
Guidelines and resources on using Artificial Intelligence (AI) for Monash students and staff are here: monash.edu/ai
Starting from a natural language question or topic, you can:
Identify relevant peer-reviewed literature from the Scopus database
Generate summaries grounded in indexed scholarly content
Explore key concepts, themes, and related research areas
Save time in literature discovery and review
Scopus AI uses generative AI to search the Scopus database and produce concise summaries of the scholarly literature relevant to your query. Responses are based on Scopus-indexed abstracts and metadata, with cited references linking directly to source documents for verification and further exploration.
Rather than relying solely on keyword matching, Scopus AI interprets the intent of your question to surface relevant publications and synthesise themes across the literature. You can refine your query conversationally, explore suggested follow-up questions, and navigate to related concepts or authors.
Scopus AI is particularly useful for:
Gaining a rapid overview of a research topic
Discovering key papers and influential work
Exploring connections between concepts or fields
Supporting early-stage literature review and topic development
By synthesising content from a large curated abstract and citation database, Scopus AI helps researchers quickly orient themselves within a field while maintaining transparency through linked source material.
Efficient and research-focused.
Starting from a simple question or topic, you can:
Identify relevant academic papers quickly
Extract and compare key findings from across studies
Explore related concepts or research questions
Save time in your literature review and evidence synthesis
Elicit uses advanced AI to search scholarly works and return a curated list of papers relevant to your query. For each paper, Elicit can highlight key information such as research questions, methods, outcomes, and sample sizes—helping you compare studies at a glance.
Rather than relying on keywords alone, Elicit interprets the intent behind your question and ranks results accordingly. You can interactively refine your query, add filters, and explore follow-up questions generated by the tool.
Elicit excels at supporting tasks like:
Generating structured evidence tables
Identifying gaps or consensus in the literature
Drafting summaries grounded in source material
By streamlining early research stages, Elicit helps you move from broad questions to focused insights—faster and with more clarity.
Fast answers from peer-reviewed sources.
Starting from a clear research question, you can:
Get concise, evidence-based answers
See how many studies support a given claim
Quickly assess the strength of the scientific consensus
Discover and compare key studies on the topic
Consensus uses AI to search and synthesise findings from peer-reviewed academic literature. It presents direct answers to your research question, along with a breakdown of supporting evidence and links to the original sources.
The tool identifies whether studies agree or disagree with the claim in question, and can highlight patterns across disciplines or over time. It’s especially useful for topics that benefit from understanding overall trends or areas of agreement in the literature.
Consensus is ideal for:
Quickly understanding what the research says
Supporting decision-making with up-to-date evidence
Comparing positions on contested or emerging issues
Interactive and exploratory.
Starting from one or more seed papers, you can:
Build dynamic maps of related research
Discover authors, co-authorship networks, and key contributors
Trace the development of ideas across time and disciplines
Explore both backward and forward citation trails
ResearchRabbit creates live, expandable graphs of related literature based on your chosen papers. As you interact with the graph, you can uncover connections between articles, authors, and fields—surfacing both well-known and unexpected research paths.
Unlike static citation maps, ResearchRabbit updates in real time as you explore, allowing you to:
Expand nodes to find related work
Track emerging trends and new publications by specific researchers
Organise your findings into custom collections
Follow author profiles and get notified of new work
The visual interface supports open-ended discovery, making it particularly useful for generating ideas, identifying collaborators, and staying current in fast-moving fields.
By combining citation data with a researcher-centric design, ResearchRabbit turns literature searching into a flexible, creative process.
Build a network of academic papers based on a paper of your choice or your current library and then analyse the network to find the most relevant literature for you. This tool allows you to discover, select and refine your topic within the tool, and then download your findings back into your reference manager. Inciteful will then provide:
Similar papers
Most important papers in the graph
Recent papers by the Top 100 Authors
The most important recent papers
These results can be further filtered by keywords (Boolean query allowed) and distance filters (basically how many citation/reference hops from the seed papers) to look for relevant papers to add as seed paper. Or you can directly add seed papers by title or DOI .
Unlike Connected Papers, which is a one shot tool, you can use Inciteful iteratively, by adding the papers it finds into the seed papers and to continue to see what it suggests.
Simple but powerful.
Starting from a single 'seed' article (or relevant article) you can:
Get a visual overview of a new academic field
Make sure you haven't missed an important paper
Discover relevant prior and derivative works
Connected papers will automatically look for about 25 papers similar to the one you chose and arrange them into a visual image with increased similarity positioned closer. The size of the node represents the number of citations and the colour shade represents the publication year.
Once you have generated the similarity graph of similar papers, you can click on either the “Prior Works” button or the “Derivative works” button to help detect seminal works or review/survey papers respectively.
For any paper identified of interest you can further click on the “build a graph” button to make it the seed paper instead and generate yet another similarity graph using it as a seed paper.
The algorithm used to calculate similarity is based on both Co-citation and similarity of references. Unlike tools that are based only on co-citations, this ensures that Connected Papers works even for very new papers that do not have many citations, as similarity of references is considered as well.