Seongmin Mun


I have taught a wide range of (under-)graduate students who are not majoring in Computational Linguistics and yet interested in computational/statistical approaches to dealing with language data. My teaching practice aims to provide students with meaningful exposure to methods and techniques for computational approaches to linguistic inquiries with a low barrier to computer languages.


All courses are conducted with student interaction through the following link.

http://seongminmun.org/chat.html



Basic Data Analysis


Ajou University, Credit: 3, March 2024 ~ Present


  • Aim: To introduce how to analyze the data by using R
  • Target: Under graduate
  • Language(s) / package(s) used: R / R basic code, ggplot2, geosphere, maps, dplyr, ggrepel, visNetwork
  • Contents: data processing / data analysis / data visualization


Materials

Class_description



Data Analytic Methodology with Digital History-Capstone Design


Ajou University, Credit: 3, September 2023 ~ December 2023


  • Aim: To introduce how to analyze language data by using R
  • Target: Under graduate
  • Language(s) / package(s) used: R / wordcloud, KoNLP, stringr, RCurl, rsconnect, shiny, etc.
  • Contents: Web crawling / POS tagging / Regular expression, Data processing, morpheme analysis, TF-IDF, Network


Materials

Class_description



Basic Data Analysis


Ajou University, Credit: 3, March 2023 ~ June 2023


  • Aim: To introduce how to analyze language data by using Python
  • Target: Under graduate
  • Language(s) / package(s) used: Python / KoNLPy, Kiwi, nltk, re, pandas, matplotlib, BeautifulSoup, wordcloud, selenium, Pyvis
  • Contents: Web crawling / POS tagging / Regular expression, Data processing, morpheme analysis, TF-IDF, Network


Materials

Class_description



Workshop: The Choson Dynasty History Association


Ajou University, June 2023


  • Title: Network Visualization for Historical Figures
  • Language(s): R


R code

R MarkDown



Research Methods for English Studies


Chosun University, Credit: 3, March 2022 ~ June 2022


  • Aim: To introduce how to analyze language data by using R & Python
  • Target: Graduate
  • Language(s) / package(s) used: R & Python / wordcloud, KoNLP, stringr, RCurl, rsconnect, shiny, pandas, konlpy, BeautifulSoup, selenium
  • Contents: Web crawling / POS tagging / Regular expression, Data processing, morpheme analysis


Materials

Class_description



R Data/Text mining & Visualization


Ajou University, January 2022 ~ February 2022


  • Aim: To introduce how to analyze language data in an R environment
  • Target: Undergraduate
  • Language(s) / package(s) used: R / wordcloud, KoNLP, stringr, RCurl, rsconnect, shiny, etc.
  • Contents: POS tagging / dependency parsing / web crawling / word cloud



Take recommendations for lunch by using Python


Chosun University, 6th ~ 7th January 2022


  • Aim: Take recommendations for lunch by using Python
  • Target: Undergraduate
  • Language(s) / package(s) used: Python / colab, pandas, konlpy, BeautifulSoup, selenium, etc.
  • Contents: Web crawling / POS tagging / Regular expression, Data processing, morpheme analysis


Resources

Description, Program


Data & Code

Github



Analyzing the distribution of linguistic elements by using spontaneous data


The phonology-morphology circle of Korea, 11st December 2021


  • Aim: To revise the written corpus to spontaneous and analyze the spontaneous data automatically
  • Target: Professor / Graduate
  • Language(s) / package(s) used: Python / colab, pandas, konlpy, jamo
  • Contents: Regular expression, Data processing, morpheme analysis


Resources

Program1, Program2, PDF


Data & Code

Github



Examine history through statistics


Korea University, October 2018 ~ November 2018


  • Aim: To create a dataset on Korean history and analyze the data automatically
  • Target: Graduate
  • Language(s) / package(s) used: R / MASS, ggplot2, scatterplot3d, lmtest, RCurl, stringr
  • Contents: web crawling / POS tagging / regression analysis / cluster analysis


Resources

Lesson1, Lesson2, Lesson3, Lesson4


Data

Ann_revised_300.csv, Ann_revised_compare.csv



Recipes: Data handling and analysis with R


Ajou University, July 2018 ~ August 2018


  • Aim: To introduce how to handle/analyze data through common data mining techniques
  • Target: Undergraduate
  • Language(s) / package(s) used: R / KoNLP, stringr, RCurl, d3Network, wordcloud
  • Contents: N-gram extraction / word cloud / network visualization


Resources

Lesson1, Lesson2, Lesson3, Lesson4


Data

Ann_revised.txt, first_assignment_after.csv, first_assignment_before.csv, heightweight.csv, mtcars.csv, UCBAdmissions.csv



Recipes: Text mining with R


Ajou University, May 2018 ~ June 2018


  • Aim: To introduce how to analyze language data in an R environment
  • Target: Undergraduate
  • Language(s) / package(s) used: R / wordcloud, KoNLP, stringr, RCurl, rsconnect, shiny
  • Contents: POS tagging / dependency parsing / web crawling / word cloud


Poster

Poster_eng, Poster_kor



Text Mining on Historical Data


Ajou University, March 2018 ~ June 2018


  • Aim: To introduce data mining techniques for historical data
  • Target: Undergraduate
  • Language(s) / package(s) used: R / wordcloud, KoNLP, stringr, RCurl, rsconnect, shiny
  • Contents: word cloud / POS tagging / dependency parsing / network visualization


Resources

Lesson1, Lesson2, Lesson3, Lesson4, Lesson5, Lesson6, Lesson7, Lesson8, Lesson9_1, Lesson9_2, Lesson10


Data

Fruits.txt, Josun.txt, Fruit_sentence.txt, GOD_1.txt, Gwanghae.txt, Thieves.txt



Text Mining on Historical Data


Ajou University, March 2016 ~ June 2016


  • Aim: To introduce data mining techniques for historical data
  • Target: Undergraduate
  • Language(s) / package(s) used: R / wordcloud, KoNLP, stringr, RCurl, rsconnect, shiny
  • Contents: word cloud / POS tagging / dependency parsing / network visualization


Resources

Lesson1, Lesson2, Lesson3, Lesson4, Lesson5, Lesson6, Lesson7, Lesson8, Lesson9, Lesson10



Data Analysis through Visualization


Lecipes, January 2016 ~ March 2016


  • Aim: To train people for acquiring commonly used data visualization techniques, in combination with statistical analysis, in order to apply this knowledge to their workplace
  • Target: Industry workers
  • Language(s) / package(s) used: R / MASS, ggplot2, lmtest, RCurl, stringr, corrplot, hebin
  • Contents: Visualization (e.g., Hitmap, Hebin, MDS), Statistics (e.g., Correlation, Regression, Cluster)


Resources

Lesson1, Lesson2, Lesson3, Lesson4, Lesson6, Lesson6, Lesson7, Lesson8



Text Mining on Historical Data


Ajou University, September 2015 ~ December 2015


  • Aim: To introduce data mining techniques for historical data
  • Target: Undergraduate
  • Language(s) / package(s) used: R / wordcloud, KoNLP, stringr, RCurl, rsconnect, shiny
  • Contents: word cloud / POS tagging / dependency parsing / network visualization


Resources

Lesson1, Lesson2, Lesson3, Lesson4, Lesson5, Lesson6, Lesson7



Visual Information Graphics


Ajou University, March 2015 ~ June 2015


  • Aim: To develop web-based data visualization systems
  • Target: Undergraduate
  • Language(s) / package(s) used: Java, JavaScript, HTML/CSS, SQL / D3.js, Jquery.js, KKMA, Eunjeon
  • Contents: Sunburst / Radial tree visualization / Sankey diagram / Parallel Coordinates


Resources

Lesson1, Lesson2, Lesson3, Lesson4, Lesson5



Visual Analysis on Historical Data


Ajou University, March 2015 ~ June 2015


  • Aim: To introduce how to apply data mining through visualization to historical data
  • Target: Undergraduate
  • Language(s) / package(s) used: R / MASS, ggplot2, KoNLP, stringr
  • Contents: Cluster analysis / MDS visualization / POS tagging


Resources

Lesson1, Lesson2, Lesson3, Lesson4




Get In Touch

If you have any interesting idea or just wanna chat, Email me!


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