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sultansaladd / NLP_bahasa_resources

A Curated List of Dataset and Usable Library Resources for NLP in Bahasa Indonesia

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NLP Bahasa Indonesia Resources

This repository provides link to useful dataset and another resources for NLP in Bahasa Indonesia.

Last Update: 22 July 2020

Dictionary

Sentiment Words

  1. (Negative) https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/negatif_ta2.txt
  2. (Negative) https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/negative_add.txt
  3. (Negative) https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/negative_keyword.txt
  4. (Negative) https://github.com/masdevid/ID-OpinionWords/blob/master/negative.txt
  5. (Positive) https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/positif_ta2.txt
  6. (Positive) https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/positive_add.txt
  7. (Positive) https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/positive_keyword.txt
  8. (Positive) https://github.com/masdevid/ID-OpinionWords/blob/master/positive.txt
  9. (Score) https://github.com/agusmakmun/SentiStrengthID/blob/master/id_dict/sentimentword.txt
  10. (InSet Lexicon) https://github.com/fajri91/InSet [Paper]
  11. (Twitter Labelled Sentiment) https://www.researchgate.net/profile/Ridi_Ferdiana/publication/339936724_Indonesian_Sentiment_Twitter_Dataset/data/5e6d64c6a6fdccf994ca18aa/Indonesian-Sentiment-Twitter-Dataset.zip?origin=publicationDetail_linkedData [Paper]

Position / Degree Words

  1. https://github.com/panggi/pujangga/blob/master/resource/netagger/contextualfeature/psuf.txt
  2. https://github.com/panggi/pujangga/blob/master/resource/netagger/contextualfeature/lldr.txt
  3. https://github.com/panggi/pujangga/blob/master/resource/netagger/contextualfeature/opos.txt
  4. https://github.com/panggi/pujangga/blob/master/resource/netagger/contextualfeature/ptit.txt

Root Words

  1. https://github.com/agusmakmun/SentiStrengthID/blob/master/id_dict/rootword.txt
  2. https://github.com/sastrawi/sastrawi/blob/master/data/kata-dasar.original.txt
  3. https://github.com/sastrawi/sastrawi/blob/master/data/kata-dasar.txt
  4. https://github.com/prasastoadi/serangkai/blob/master/serangkai/kamus/data/kamus-kata-dasar.csv

I have made the combined root words list from all of the above repositories.

Slang Words

  1. https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/kbba.txt
  2. https://github.com/agusmakmun/SentiStrengthID/blob/master/id_dict/slangword.txt
  3. https://github.com/panggi/pujangga/blob/master/resource/formalization/formalizationDict.txt

I have made the combined slang words dictionary from all of the above repositories.

Stop Words

  1. https://github.com/yasirutomo/python-sentianalysis-id/blob/master/data/feature_list/stopwordsID.txt
  2. https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/stopword.txt
  3. https://github.com/abhimantramb/elang/tree/master/word2vec/utils/stopwords-list

I have made the combined stop words list from all of the above repositories.

Emoticon

  1. https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/emoticon.txt
  2. https://github.com/jolicode/emoji-search/blob/master/synonyms/cldr-emoji-annotation-synonyms-id.txt
  3. https://github.com/agusmakmun/SentiStrengthID/blob/master/id_dict/emoticon.txt

Acronym

  1. https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/acronym.txt
  2. https://github.com/panggi/pujangga/blob/master/resource/sentencedetector/acronym.txt
  3. https://id.wiktionary.org/wiki/Lampiran:Daftar_singkatan_dan_akronim_dalam_bahasa_Indonesia#A

Indonesia Region

  1. https://github.com/abhimantramb/elang/blob/master/word2vec/utils/indonesian-region.txt
  2. https://github.com/edwardsamuel/Wilayah-Administratif-Indonesia/tree/master/csv
  3. https://github.com/pentagonal/Indonesia-Postal-Code/tree/master/Csv

Swear Words

  1. https://github.com/abhimantramb/elang/blob/master/word2vec/utils/swear-words.txt

Composite Words

  1. https://github.com/panggi/pujangga/blob/master/resource/tokenizer/compositewords.txt

Country

  1. https://github.com/panggi/pujangga/blob/master/resource/netagger/contextualfeature/country.txt

Region Words

  1. https://github.com/panggi/pujangga/blob/master/resource/netagger/contextualfeature/lpre.txt

Title of Name Words

  1. https://github.com/panggi/pujangga/blob/master/resource/netagger/contextualfeature/ppre.txt

Gender by Name

  1. https://github.com/seuriously/genderprediction/blob/master/namatraining.txt

Organization Words

  1. https://github.com/panggi/pujangga/blob/master/resource/reference/opre.txt

Number Words

  1. https://github.com/panggi/pujangga/blob/master/resource/netagger/morphologicalfeature/number.txt

POS-Tagging

  1. https://medium.com/@puspitakaban/pos-tagging-bahasa-indonesia-dengan-flair-nlp-c12e45542860
  2. Manually Tagged Indonesian Corpus [Paper] [GitHub]

Pre-trained word embedding

  1. Generate Word-Embedding / Sentence-Embedding using pre-Trained Multilingual Bert model. (https://colab.research.google.com/drive/1yFphU6PW9Uo6lmDly_ud9a6c4RCYlwdX#scrollTo=Zn0n2S-FWZih). P.S: Just change the model using 'bert-base-multilingual-uncased'
  2. https://github.com/meisaputri21/Indonesian-Twitter-Emotion-Dataset. [Paper]
  3. https://github.com/Kyubyong/wordvectors
  4. https://drive.google.com/uc?id=0B5YTktu2dOKKNUY1OWJORlZTcUU&export=download
  5. https://github.com/deryrahman/word2vec-bahasa-indonesia
  6. https://sites.google.com/site/rmyeid/projects/polyglot

Train Word Embedding by Your Self

  1. (FastText). https://structilmy.com/2019/08/membuat-model-word-embedding-fasttext-bahasa-indonesia/
  2. (Word2Vec). https://yudiwbs.wordpress.com/2018/03/31/word2vec-wikipedia-bahasa-indonesia-dengan-python-gensim/

Usable Library

  1. Pujangga: Indonesian Natural Language Processing REST API. https://github.com/panggi/pujangga
  2. Sastrawi Stemmer Bahasa Indonesia. https://github.com/sastrawi/sastrawi
  3. NLP-ID. https://github.com/kumparan/nlp-id
  4. MorphInd: Indonesian Morphological Analyzer. http://septinalarasati.com/morphind/
  5. INDRA: Indonesian Resource Grammar. https://github.com/davidmoeljadi/INDRA
  6. Typo Checker. https://github.com/mamat-rahmat/checker_id
  7. Multilingual NLP Package. https://github.com/flairNLP/flair
  8. spaCy [GitHub] [Tutorial]
  9. https://github.com/yohanesgultom/nlp-experiments
  10. https://github.com/yasirutomo/python-sentianalysis-id
  11. https://github.com/riochr17/Analisis-Sentimen-ID
  12. https://github.com/yusufsyaifudin/indonesia-ner

Topic Analysis

  1. (Introduction to LSA & LDA). https://monkeylearn.com/blog/introduction-to-topic-modeling/
  2. (Introduction to LDA w/ Code & Tips). https://www.analyticsvidhya.com/blog/2016/08/beginners-guide-to-topic-modeling-in-python/
  3. (Topic Modeling Methods Comparison Paper). https://thesai.org/Downloads/Volume6No1/Paper_21-A_Survey_of_Topic_Modeling_in_Text_Mining.pdf
  4. (Original LDA Paper). http://www.jmlr.org/papers/volume3/blei03a/blei03a.pdf
  5. (LDA Python Library). https://pypi.org/project/lda/; https://radimrehurek.com/gensim/models/ldamodel.html; https://scikit-learn.org/stable/modules/generated/sklearn.decomposition.LatentDirichletAllocation.html
  6. (Original CTM Paper). http://people.ee.duke.edu/~lcarin/Blei2005CTM.pdf
  7. (CTM Python Library). https://pypi.org/project/tomotopy/; https://github.com/kzhai/PyCTM
  8. (Gaussian LDA Paper). https://www.aclweb.org/anthology/P15-1077.pdf
  9. (Gaussian LDA Library). https://github.com/rajarshd/Gaussian_LDA
  10. (Temporal Topic Modeling Comparison Paper). https://thesai.org/Downloads/Volume6No1/Paper_21-A_Survey_of_Topic_Modeling_in_Text_Mining.pdf
  11. (TOT: A Non-Markov Continuous-Time Model of Topical Trends Paper). https://people.cs.umass.edu/~mccallum/papers/tot-kdd06s.pdf
  12. (TOT Library). https://github.com/ahmaurya/topics_over_time
  13. (Example of LDA in Bahasa Project Code). https://github.com/kirralabs/text-clustering

Translation

Sometimes there is an english word within our text and we have to translate it. We can exploit the english word dictionary provided here and we can use the Google Translate API for Python

Spelling Correction

You can adjust this code with Bahasa corpus to do the spelling correction

Twitter Scraping:

  1. GetOldTweets3. https://github.com/Mottl/GetOldTweets3

Usage:

import GetOldTweets3 as got
tweetCriteria=got.manager.TweetCriteria().setQuerySearch('#CoronaVirusIndonesia').setSince("2020-01-01").setUntil("2020-03-05").setNear("Jakarta, Indonesia").setLang("id")
tweets=got.manager.TweetManager.getTweets(tweetCriteria)
for tweet in tweets:
	print(tweet.username)
	print(tweet.text)
	print(tweet.date)
	print("tweet.to")
	print("tweet.retweets")
	print("tweet.favorites")
	print("tweet.mentions")
	print("tweet.hashtags")
	print("tweet.geo")
  1. Tweepy. http://docs.tweepy.org/en/latest/

Step-by-step how to use Tweepy. https://towardsdatascience.com/how-to-scrape-tweets-from-twitter-59287e20f0f1

Sign in to Twitter Developer. https://developer.twitter.com/en

Full List of Tweets Object. https://developer.twitter.com/en/docs/tweets/data-dictionary/overview/tweet-object

Increasing Tweepy’s standard API search limit. https://bhaskarvk.github.io/2015/01/how-to-use-twitters-search-rest-api-most-effectively./

Other Resources:

  1. https://github.com/irfnrdh/Awesome-Indonesia-NLP

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A Curated List of Dataset and Usable Library Resources for NLP in Bahasa Indonesia

License:MIT License