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If you really want to get to know all the functionality of Inciteful, you’ve found the right place.

Beta Features

Community feedback is invaluable. That’s why you can opt into features we are testing from our Beta Features page. Go boldly forth if you are the adventurous type.

Graph Filters

On every graph dashboard there are a set of filters which allow you to filter the contents of the tables below. This allows you to really dig into the graph and find the type of papers you are looking for. The three types of filters are keywords, distance, and year.

The year filter is pretty straight forward it filters on the year the paper was published. The other two need a bit more explaining.

Keyword Filters

The keyword filters do just that, they filter on keywords present in the title. Unfortunately we do not have access to abstracts at this point and so title filtering is the best we can do.

We tried to make the search flexible.

Boolean Queries

The keyword filter does do Boolean queries. So you can use the AND, OR, and NOT in your queries. The following are all valid queries:

hello AND world
foo OR bar
(goodbye AND world) NOT cruel

You can join them together to your heart’s content.

Porter Stemming

Also, the keywords you put in are subject to the Porter Stemming Algorithm so that it will do partial matches on words. For example, the following words would all match each other with the same stem of connect:

connect
connected
connecting
connection
connections

Distance Filters

In order to really understand the distance filters you first need to understand how the graphs are constructed. But I will do a quick rundown here.

For graphs that are centered on a single seed paper:

  • the seed paper has a distance of 0
  • papers which either cite the seed paper or are cited by the seed paper have a distance of 1
  • papers which either cite or are cited by the papers with a distance of 1, have a distance of 2

In visual form:

For papers which are centered around multiple seed papers:

  • the “fake paper” we create has a distance of 0
  • the seed papers have a distance of 1
  • papers which either cite or are cited by the seed papers have a distance of 2

For a better understanding, head over to the how does Inciteful work page.

BibTeX

Inciteful supports both BibTeX importing as well as exporting. The import functionality is used to seed a graph and the export functionality is used to save papers that are of interest to you.

Importing into Inciteful

Instead of manually building up your network, you can use the import functionality to seed a network with papers in which you are already interested. In order to do so, go to the home page and under the main search box there is an Import BibTeX link. Click on that to use your BibTeX file as the basis for your search.

Note: Inciteful will only recognize BibTeX entries with a DOI associated with them. So please be sure that your references have the appropriate DOIs. If using Zotero, you can use the Locate functionality to expedite this process.

Mendeley: Exporting Citations to a BibTex file

  1. Select the references you wish to export to BibTex in Mendeley
  2. Under the File menu item click Export
  3. Then choose file type BibTex (*.bib), save your BibTex file with a .bib extension

Zotero: Exporting Citations to a BibTex file

  1. Under the My Library menu on the left, right click on the folder you wish to export.
  2. In the context menu click Export Collection
  3. Then choose the BibTex format and click OK
  4. Save your BibTex file with a .bib extension

Exporting from Inciteful

At the bottom of every table which has a DOI in the data, there will be an export button () which you can use to export the contents of the table in a BibTeX format.

SQL Query Panel

Database Schema

The following is the schema for the database which you query. Every graph has a corresponding unique database.

papers

The table containing all of the papers in the graph

Column Name Type Description
paper_id INTEGER The unique id of the paper.
doi TEXT The doi of the paper in question.
authors TEXT A json field of all the authors on the paper.
title TEXT The title of the paper.
published_year INTEGER The year the paper was published.
published_month INTEGER The month the paper was published.
journal TEXT The journal in which the paper was published.
volume TEXT The volume of the journal in which the paper was published.
issue TEXT The issue of the journal in which the paper was published.
book_title TEXT The title of the book in which the paper was published.
num_citing INTEGER The number of papers which this papers cites.
num_cited_by INTEGER The number of papers which cite this paper.
distance INTEGER The distance away (as an undirected graph) this paper lies from the seed paper.
page_rank REAL The PageRank of this paper.
adamic_adar REAL The Adamic/Adar score of the paper. Adamic/Adar is a link prediction algorithms which, when used in this context, can help to detect similarity between papers.
resource_allocation REAL Similar to Adamic/Adar, the Resource Allocation score of the paper is a link prediction algorithms which, when used in this context, can help to detect similarity between papers.
conference_series_name TEXT The name of the conference in which the paper was presented.
conference_instance_name TEXT The instance of the conference in which the paper was presented. This is more specific than the conference_series_name
conference_location TEXT The location of the conference where the paper was presented.
conference_year TEXT The year of the conference where the paper was presented.

authors

A denormalized table containing the metadata about each author for each paper.

Column Name Type Description
author_id INTEGER The unique id of the author.
paper_id INTEGER The unique id of the paper.
name TEXT The name of the author.
sequence INTEGER The sequence of the author in the paper.
affiliation TEXT The affiliation of the author at the time the paper was written

title_search('SEARCH_TERM')

A table containing a full text index of the paper titles that can be searched by replacing {SEARCH_TERM} with the query of your choice. You can use Boolean operators like AND, OR, and NOT in addition to parenthesis to create matching logic. An example finding the best match:

SELECT * FROM title_search('refugee') ORDER BY bm25(title_search)
Column Name Type Description
paper_id INTEGER The unique id of the paper.
title TEXT The text which was searched.
bm25(title_search) REAL Returns a real value indicating how well the current row matches the full-text query. The better the match, the numerically smaller the value returned.

title_terms

A table a list of all of the stemmed title terms present in the full text index and their counts.

Column Name Type Description
term TEXT The porter-stemmed terms which appear in the titles.
doc_count INT The number of papers in which these terms appear.

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