-
Notifications
You must be signed in to change notification settings - Fork 0
/
presentation.qmd
86 lines (60 loc) · 2.1 KB
/
presentation.qmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
---
title: "Text Analysis and NLP Techniques in Practice"
author: "Manu Alcalá Kovalski and Judah Axelrod"
title-slide-attributes:
data-background-color: "#1696d2"
format:
revealjs:
logo: www/images/urban-institute-logo.png
incremental: true
editor: visual
output:
html:
number_sections: FALSE
self_contained: TRUE
code_folding: hide
toc: TRUE
toc_float: TRUE
mathjax: null
df_print: paged
css: !expr here::here("www", "web_report.css")
editor_options:
chunk_output_type: console
---
## Locate keywords
::: columns
::: {.column .incremental width="40%"}
- Parse corpus of documents
- Create dictionary of keywords
- Find keywords across entire corpus or within a context
:::
::: {.column width="50%"}
![](images/DOL-eap.png){fig-align="center"}
:::
:::
------------------------------------------------------------------------
## Dictionary
![](images/communities-dictionary.png){.r-stretch width="90%"}
------------------------------------------------------------------------
## Global Search
![](images/communities-frequency-global-eap.png)
------------------------------------------------------------------------
## Window Search
![Searched for vulnerable communities within 20 words of mentions of
underserved, underrepresented, overburdened, vulnerable, marginalized,
disadvantaged, or communities of
concern.](images/communities-frequency-window-eap.png)
------------------------------------------------------------------------
## Topic Modeling
![Figure source: Blei, D.M (2012). Probabilistic topic models.
*Communication of the ACM 55*(4),
77-84.](images/topic-models-blei-2012.png)
------------------------------------------------------------------------
## Topics for AP News articles
![](images/ap-top-terms.png){width="100%" fig-align="center"}
------------------------------------------------------------------------
## Analyzing Twitter Trends
![](images/biden-tweet-freqs.png)
------------------------------------------------------------------------
## Sentiment Analysis
![](images/sentiment-analysis-trend.png){width="80%" fig-align="center"}