For article-based analysis, use the local citation network (timwoelfle.github.io/Local-Citation…) to see the whole citation (and co-authorship) network of a study
Paste DOI of an article you'd like a network for, and enjoy
4. Check what part of the article is most cited and with which sentiment
scite.ai shows the statements in which the article has been cited and estimates whether citing authors supported or negated the argument
5. Analyze the collected articles
Even if you have no experience in text mining, GATE (gate.ac.uk) will help you analyze the articles for lit review and solve almost any text-processing problem
Read their user guide for a smooth start
6. Report your lit review findings
Bit.ai is a cloud-based platform that allows you to store relevant research and share it with your co-authors in real time
Is it better than google drive? Not entirely sure but give it a try
To sum up:
1. Query with @2d_search 2. Research domain summary with @TheIrisAI 3. Citation network with local citation network (@timwoelfle) 4. Article citations with @scite 5. Text-mining with GATE 6. Reporting with @Bit_docs
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🔺 litmaps.com: shows you all the articles on your topic and cross-citation. Search using keywords, DOI, titles, and authors to visualize your field of interest
🔺 openknowledgemaps.org: comprehensively maps your research topic by 1) showing the main research streams within it, 2) identifying all relevant concepts and terms, and 3) clustering similar articles to make learning easier. It's a must!
1. No onboarding, having to piece together all the info
How do the printers work? What is FAIR data? For most of us, there was no comprehensive onboarding that'd explain how the academic environment works
💡Tip: team up with a more senior PhD student to get some lifehacks
2. Feeling frustrated, lost, lacking progress
Most of us have to define the project ourselves. An overwhelming amount of information and no clear "rules of the game" take their toll
💡Tip: narrow down, define your niche, read the best articles from your field, get feedback early
1⃣ Data challenges: new privacy regulations, no access to third-party cookies, and new post-covid advertising models
Some research questions to look at:
• What business models can help companies adapt to changing privacy policies?
• What available data (e.g., search data) should firms use to improve targeting?
• Can firms optimally combine pre and post covid advertising models?