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Get food & name tag
Sit next to people you don’t know

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Today: Strategies for a literature search

But before that, recap:

What were everyone’s takeaways from two classes ago about how to skim a paper?

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Today: Strategies for a literature search

But before that, recap:

What were everyone’s takeaways from two classes ago about how to skim a paper?
What are some takeaways from the pre-class work about citation patterns and knowledge diffusion in science?

General takeaways about citation patterns: We find that idiosyncratic citation patterns are characteristic for low impact papers; while narrow, discipline-focused citation patterns are common for medium impact papers. Our results show that crossingcommunity, or bridging citation patters are high risk and high reward since such patterns are characteristic for both low and high impact papers. Last, we observe that recently citation networks are trending toward more bridging and interdisciplinary forms.

In CS: For example, computer science behaves differently, as high impact papers there tend to have very focused citation networks mostly referring to papers from a narrow community. However, analyses of temporal trends of citation behaviors reveal that both natural and computer science are getting more interdisciplinary over time as the citation networks are getting more diverse and papers from multiple communities are cited.

We found that the ways ideas become relationally situated in their ideational ecology is especially decisive for their long-run career. Ideas tend to diffuse more broadly when their authors link them to prominent, foundational ideas within science, consistently interrelate and position them within an established network of ideas, and thickly interrelate them—filling out research topics and networks with greater links. We also found that the successful diffusion of ideas depends on their social ecology, that is, the communities of scholars who take them up. Specifically, new ideas tend to diffuse when focally central researchers publish on them and when those authors span diverse research communities.

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Today: Strategies for a literature search (Sonja)

What is the purpose of a literature search?
What makes a literature search hard?

Orienting yourself in an unfamiliar field
Filtering hundreds of papers
Organizing the papers you’ve read

What do you find hard?

Fear of misunderstanding the paper
Fear of missing important work

Seminal works?
Comprehensive lit review?
Parallel fields?

How can I make sure I don’t cite for the sake of citing?

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The ins-and-outs of a literature search

(1)

Refining search criteria

Brainstorm project

Project topic

Keywords

(2)

Categorizing a paper

Google

Papers

Reading*

Reading goal

(3)

Tracking papers

Summary

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Tools for searching papers

Google Scholar
Semantic Scholar
Your favorite tools for finding new or related papers?

Collaborators, senior students/postdocs
Slacks (not necessarily your lab) for papers of interest
Websites for specific field
Surveys + review papers
Class syllabi + slides
Papers you like → First authors → lab website → lab papers
(arXiv, semantic scholar) daily digest
Non-terrible AI newsletters
ChatGPT for keyword generation

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Component 1: Refining your search criteria (Sonia)

(1)

Refining search criteria

Google

Brainstorm project

Project topic

Keywords

Goal: break down your project topic into a list of precise keywords that will return relevant papers on the topic upon search.

Performance: help-seeking by asking another person for good keywords

How to turn whatever idea or understanding of your project is in your head, into the appropriate search queries to make use of search engines.
This process can be started by looking at papers and keywords recommended to you by others, but can be challenging because it requires a conceptual redefinition of your understanding of the project in response to new literature you see
One thing that came up recently in my work was that I thought I went through the literature search process and found all the papers, but then my advisor suggested a

So, at this first step of the process we can think of the input being

In: A project statement, likely in the form of a high-level motivation and desired outcome
Out: A set of keywords that will lead to relevant papers in a google search�Tip: Ask colleagues/mentors familiar with your line of work for a suggested set of keywords

At this first step of the literature search, you probably have a rough idea of what kind of problem setting you’re in but need precision to best utilize search engines like Google Scholar. This is the part where you associate your broad question with a set of keywords.

Sometimes you may stumble upon the appropriate keywords with a few minutes of searching on google; however, often you may not. This is normal – consider asking colleagues/mentors in the relevant field for a suggested set of keywords (or for some keywords to avoid and why). Even better, they may be able to recommend you some relevant papers to start with.

What are some other goals one could set, besides turning up a good search?

What are some ways to make this easier?

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In groups of 5: what are good keywords for this problem?

Problem: There is significant bias in the data collection used Genome-Wide Association Studies (GWAS) towards populations that identify as of European ancestry. As a result, statistical models of the data are substantially less predictive for populations identifying as of non-European ancestry.

Significance: Increased health disparities between populations identifying as of European vs. non-European ancestry.

Goal: To develop statistical methodology capable of both using existing data and effectively leveraging data from a more inclusive collection process to generalize well to populations identifying as of non-European ancestry.

*you can use Harvard Hollis to get behind paywalls when trying to access papers (instructions here)

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Regroup

What were the keywords found?
How did you find them?
How did you know they were relevant?
What was hard about this?

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Component 2: Categorizing your papers (Sonja)

(2)

Categorizing a paper

Reading*

Papers

Searching your keywords
Going “up” the citation tree
Going “down” the citation tree
Following the author/lab group, not just the citations

Reading goal

Goal: Figure out which papers to read, how much to focus on each paper, and what to read for.

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Component 2: Categorizing your papers

How is this paper relevant to my research topic?

Read for a problem statement + importance

Read for feasibility

Read for understanding

Is this paper relevant to my project topic?

No

Yes

Solves same problem

Solves similar problem

Solves subproblem

Read for a contrastive sentence

Motivates my problem

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In groups of 5: which papers are relevant? How did you know?

tinyurl.com/5z78mzda

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In groups of 5: how would you categorize the papers?

Motivates the problem
Solves the same problem
Solves a similar problem
Solves a subproblem

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Component 3: Tracking papers (Sonja)

Tools of the trade: citation managers (Zotero, Mendeley, EndNote)
Google Scholar Extension, helps you double check
A searchable document to keep summaries

Google Docs, Obsidian, Notion

What to put in each summary? Consider:

Problem statement (one sentence)
Relevance to project (same problem, similar problem, or sub-problem)?
Brief description: usually one sentence of contributions/explanation of how it relates to my paper.

Self-reflection: self-evaluation of whether a certain system works for you and how to adapt

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Announcements

Next week: how to deep read a paper
Course website has in-depth material from class today
Navigating SEAS event Monday 10/7 at 2:15pm

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Self-regulated learning for literature search

	Forethought	Performance	Self-reflection
Refining search criteria	Goals?	Help-seeking	Evaluation?
Categorizing a paper	Goals?	Time management	Evaluation?
Tracking your papers	Goals?	Self-consequences	Evaluation?

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In-class exercise: refining your search in pairs

(Pull out your laptops)

Break out into pairs (or trios) at your table
Read each other your pre-class work response to the question #4: brief description of a research project topic
Time to Google! Come up with a list of keywords on your partner’s project topic
Show one another your list of keywords. Get feedback; would searching for these terms get you relevant papers?

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Regrouping: refining your search in pairs

What was your strategy?
What went wrong?
What went well?

How many people asked the other person for a suggested set of keywords to start?