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<!DOCTYPE html>
<html lang="" xml:lang="">
<head>
<title>Advanced String Processing with stringi</title>
<meta charset="utf-8" />
<meta name="author" content="Benedict Anderer" />
<meta name="author" content="Farhan Shaikh" />
<meta name="author" content="Saurav Jah" />
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class: center, middle, inverse, title-slide
.title[
# Advanced String Processing with <code>stringi</code>
]
.subtitle[
## Live Workshop Session
]
.author[
### Benedict Anderer
]
.author[
### Farhan Shaikh
]
.author[
### Saurav Jah
]
.institute[
### <strong>Hertie School of Governance, Berlin</strong>
]
.date[
### 2024/10/28 (updated: 2024-10-28)
]
---
# Outline
1. Text as Data in R
--
<br>
2. String Processing in the Political Sciences
--
<br>
3. Introducing `stringi` & Friends
--
<br>
4. Key Features & Use Cases
--
<br>
5. Match Made in Heaven: `stringi` & Regex
--
<br>
6. Further Resources
---
#Text as Data in R
Example of text data in R:
--
```r
text_as_vector<- c("NLP is a subfield of artificial intelligence", "Text data is crucial for analysis.")
text_with_special_characters<-"Check out #RStats and #DataScience! Ämäzîng!"
text_with_uneven_spaces<-"All code chunk outputs presented in this paper were obtained in R 4.1.2."
```
###Common Elements of Textual Data Analysis:
- Data cleaning and preprocessing
- Pattern matching
- Multilingual text handling
---
#Text as Data in R
##Significance of text data in the context of Data Science
.pull-left[
- Ever heard of the term, Natural Language Processing or NLP?
- at the core: textual analysis
- issue: most text data, especially when scraped from internet, is **messy**.
<img src="images/mess.gif" width="80%" />
]
--
.pull-right[
- But ultimately text is data and Stringology is the science of dealing with it (cf. [Crochemore and Rytter 2003](https://www.sciencedirect.com/science/article/pii/S030439750200590X), [Jurafsky and Martin 2008; Szpankowski 2001](https://www.researchgate.net/publication/200111340_Speech_and_Language_Processing_An_Introduction_to_Natural_Language_Processing_Computational_Linguistics_and_Speech_Recognition))
- Dedicated tools in R for effectively manipulating, cleaning and analyzing textual data: `stringi` and `stringr`
]
--
<div class="logo-right">
<img src="images/stringi.png" alt="Stringi Logo" />
</div>
<div class="logo-left">
<img src="images/stringr.png" alt="Stringr Logo" />
</div>
---
#String Processing in the Political Sciences
.pull-left[
In the political sciences, we study textual data from:
- Political speeches, manifestos, and debates
- Social media and news articles
- Surveys and interviews
A growing body of research in comparative politics make use of text mining and regular expressions:
- [The Manifesto Project Database](https://manifesto-project.wzb.eu) studies ideological shifts in party manifestos
- [Eckhard et al. (2021)](https://www.polver.uni-konstanz.de/eckhard/research/current-research-projects/text-as-data-the-evolution-of-the-un-security-council-debates-1995-2017/) studied the evolution of the UN Security Council debates based on all speeches from 1995-2017
- [Soroka (2012)](https://psycnet.apa.org/record/2012-10832-011) analyzed the issue framing and tone in the media towards political candidates during elections across countries
]
.pull-right[
<img src="images/neuland.gif" width="120%" />
]
---
#Introducing `stringi` & Friends
##String processing in the tidyverse
<div class="logo-right">
<img src="images/stringi.png" alt="Stringi Logo" />
</div>
- unlike `base`, `stringi`follows a `tidyverse`-syntax
--
- most comprehensive string processing package (250 functions)
--
- commands begin with `stri`
- less accessible, but can handle advanced tasks
- relies on International Components for Unicode (ICU)
--
<br>
<div class="logo-left">
<img src="images/stringr.png" alt="Stringr Logo" />
</div>
- `stringr`: based on `stringi`
--
- more accessible, but "only" 49 functions
- commands begin with `str`
---
#Introducing `stringi` & Friends
##Why you should use `stringi`
<div class="logo-right">
<img src="images/stringi.png" alt="Stringi Logo" />
</div>
- `stringi` supports [Unicode](https://home.unicode.org) ➡️ can process text & date data in different locales which is important for working data with from different countries. **Examples**:
--
```r
x <- "28 października 2024 r., godz. 17:10:00"
stringi::stri_datetime_parse(x, "dd MMMM yyyy 'r., godz.' HH:mm:ss",locale="pl_PL", tz="Europe/Warsaw")
```
```
## [1] "2024-10-28 17:10:00 CET"
```
```r
stringi::stri_trans_general("Droga Użytkowniczko, Drogi Użytkowniku, jeśli wyrazisz zgodę klikając", "latin-ascii")
```
```
## [1] "Droga Uzytkowniczko, Drogi Uzytkowniku, jesli wyrazisz zgode klikajac"
```
--
- the most versatile string-processing package:
--
if you are struggling to achieve your goals with `base`or `stringr`, <br>
take a look at `stringi`resources (e.g. [this](https://www.rdocumentation.org/packages/stringi/versions/1.8.4) or [this](https://stringi.gagolewski.com/index.html))
---
#Key Features & Use Cases
.pull-left[
**1. Working with temporal data from different locales:**
<br>
use `stri_datetime_parse`to homogenize temporal data.
<br>
*Example*: You scraped flight schedules from different countries and want to homogenize the notation of time and date.
<br>
<img src="images/dates.jpg" width="40%" />
]
--
.pull-right[
**2. General Transforms:** <br>
use `stri_trans_general` to transliterate characters from one script to another script of your choosing.
<br>
*Example*: You might be working with data from a foreign local and the special characters are not displaying well. You can use `stri_trans_general` to convert them to Latin-ASCII.
```r
library("stringi")
stri_trans_general("Dämliche Düsen lärmen prächtig", "latin-ascii")
```
```
## [1] "Damliche Dusen larmen prachtig"
```
]
---
#Key Features & Use Cases continued
.pull-left[
<img src ="images/split.jpg" width="20%" />
<br>
**3. Text Boundary Analysis:**<br>
To split text into lines/words/characters, count characters or locate particular text units (e.g. the 4th word of a sentence), use commands like `stri_count_boundares`, `stri_split_boundaries` or `stri_locate_boundaries`.
<br>
*Example*: To prepare text data for a bag of words analysis ➡️ use `stri_split_boundaries`to split the text into words.
]
--
.pull-right[<img src ="images/replace.jpg" width="20%" />
<br>
**4. Extracting & Replacing Substrings:** <br>
use `stri_sub`to extract and replace substrings.
<br>
*Example*: If you have a data set with telephone numbers and want to standardize them or want to extract information like country or area code. It is also handy for anonymizing personal data.
]
---
#Key Features & Use Cases continued
.pull-left[
<img src ="images/glue.jpg" width="20%" />
<br>
**5. Concatenating Strings:** <br>
to run concatenation-based operations, use `stri_join`, `stri_dup`, %s+%, or `stri_flatten`.
<br>
*Example*: You might want to create a key for observations by concatenating multiple variables. It is also helpful for building URLs when scraping.
]
--
.pull-right[
<img src ="images/trim.jpg" width="20%" />
<br>
**6. Trimming:** <br>
to remove uneccessary white spaces, use `stri_trim`.
<br>
*Example*: You've scraped text from the web and need to remove superfluous white spaces at the beginning and/or end of the strings.
]
---
#Match Made in Heaven: Stringi & Regex
##Portability and Versatility
- As `stringi` is an extension of `stringr` with Unicode standards, it uses the same Regex syntax for pattern matching, subsetting, and any other textual analysis.
--
- Regex allows for a variety of operations: subsetting, cleaning, pattern matching, text substitution and replacement, case conversion
--
##Major Functions:
.pull-left[
- `stri_detect_regex()` – Detecting Patterns in Text
- `stri_extract_all_regex()` – Extracting Matching Substrings
- `stri_replace_all_regex()` – Replacing Patterns
]
--
.pull-right[
- `stri_count_regex()` – Counting Matches in Text
- `stri_split_regex()` – Splitting Text by Pattern
- `stri_match_all_regex() `– Extracting Groups of Matches
- `stri_locate_all_regex()` – Locating Pattern Matches
]
---
#Further Resources
If you're interested in learning more about `stringi`, feel free to check out the following resources:
- [Overview of key functions 1](https://www.rdocumentation.org/packages/stringi/versions/1.8.4/topics/about_stringi)
- [Overview of key functions 2](https://stringi.gagolewski.com/index.html#)
- [CRAN entry](https://cran.r-project.org/web/packages/stringi/index.html)
- [Paper by the package's author](https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://www.jstatsoft.org/article/view/v103i02/4324&ved=2ahUKEwjznajP1qKJAxUN9AIHHR-AH0oQFnoECB4QAQ&usg=AOvVaw2ysoUKJIt6sqvLBgWUotez)
- [Documentation](https://www.rdocumentation.org/packages/stringi/versions/1.8.4)
- [`stringi`Github repo](https://github.com/gagolews/stringi)
---
#Image Credits
- [`stringi`logo](https://www.google.com/url?sa=i&url=https%3A%2F%2Fstringi.gagolewski.com%2F&psig=AOvVaw3_xTop87NlWBu_Ek9kc9A6&ust=1729697796955000&source=images&cd=vfe&opi=89978449&ved=0CBEQjRxqFwoTCNDOmMmoookDFQAAAAAdAAAAABAE)
- [`stringr`logo](https://www.google.com/url?sa=i&url=https%3A%2F%2Fstringr.tidyverse.org%2F&psig=AOvVaw1zAo-FsdcgSe-wNVp_QlHz&ust=1729795760171000&source=images&cd=vfe&opi=89978449&ved=0CBEQjRxqFwoTCKDatcKVpYkDFQAAAAAdAAAAABAE)
- [mess-GIF](https://www.google.com/url?sa=i&url=https%3A%2F%2Ftenor.com%2Fsearch%2Fhuge-mess-gifs&psig=AOvVaw1IetlpzB_oQU8hF8sCjEkT&ust=1729795796396000&source=images&cd=vfe&opi=89978449&ved=0CBMQjRxqFwoTCLj6ztGVpYkDFQAAAAAdAAAAABAj)
- [Merkel-GIF](https://www.google.com/url?sa=i&url=https%3A%2F%2Ftenor.com%2Fsearch%2Fangela-merkel-gifs&psig=AOvVaw2tejlmj8ycQsAXH5uiWpAd&ust=1729797841025000&source=images&cd=vfe&opi=89978449&ved=0CBMQjRxqFwoTCJD4rKGdpYkDFQAAAAAdAAAAABAj)
</textarea>
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