Andy Halterman (@ahalterman)
  • Stars
    star
    244
  • Global Rank 104,772 (Top 4 %)
  • Followers 163
  • Following 8
  • Registered over 11 years ago
  • Most used languages
    Python
    52.9 %
    R
    29.4 %
    Shell
    5.9 %
    HTML
    5.9 %
  • Location ๐Ÿ‡บ๐Ÿ‡ธ United States
  • Country Total Rank 27,401
  • Country Ranking
    R
    1,175
    HTML
    2,777
    Shell
    5,830
    Python
    7,768

Top repositories

1

mordecai3

Full text geoparsing/toponym resolution with event geolocation
Python
67
star
2

multiuser_prodigy

Running Prodigy for a team of annotators
HTML
53
star
3

CLIFF-up

Set up MIT's CLIFF geolocation service with Vagrant
Shell
17
star
4

cloacina

Tools for downloading from the LexisNexis API
Python
17
star
5

NGEC

A new, machine learning-based pipeline for extracting political events from text
Python
17
star
6

gdeltr

R tools for GDELT and the Global Knowledge Graph
R
14
star
7

phoxy

R tools to download, ingest, and analyze the Phoenix dataset from the Open Event Data Alliance
R
12
star
8

prodigy_guide

Guides for using Prodigy, a data annotation tool for machine learning
Python
7
star
9

learn_to_scrape

Materials for MIT Methods Lab workshop on learning to scrape
Jupyter Notebook
6
star
10

GKG-Themes

The keywords used to generate themes for the GDELT Global Knowledge Graph.
5
star
11

event_location

Data for "Geolocating Political Events in Text"
5
star
12

VSS

Extract news stories from LexisNexis Bulk API dumps
Python
5
star
13

night_ridir

Containerized tools for event data dictionary development
Python
2
star
14

cloacina2

Download stories from the LexisNexis WSK API with rate limits
Python
2
star
15

general_examiner

Tools for studying for general exams
Python
1
star
16

bikes

A data-only R package with 848,755 rides in the Capital Bikeshare system
R
1
star
17

538_state_corr

Explore state-level correlations in the 538 model
R
1
star
18

train_word2vec

Tools for training new word2vec models
Python
1
star
19

ISA-2014

Replication materials for Halterman and Irvine 2014 ISA paper.
R
1
star