As part of preparedness efforts in dealing with this, it is important for Indonesia to prepare guidelines for preparedness in dealing with COVID-19.

Instructions: 

This guideline is intended for health workers as a reference in preparing for COVID-19. This guideline is provisional because it has been prepared by adopting WHO interim guidelines so that it will be updated in accordance with disease developments and the current situation.

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Enrichment analysis performed by Enrichr toward genes associated with coronavirus infeciton

Instructions: 

Genes are selected by TD based unsupervised FE and are uploaded to Enrichr

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Free dataset from news/message boards/blogs about CoronaVirus (4 month of data - 5.2M posts). The time frame of the data is Dec/2019 - March/2020. The posts are in English mentioning at least one of the following: "Covid" OR CoronaVirus OR "Corona Virus".

 

Instructions: 

The data is stored inside a zip file that contains a JSON file. Here is an example of a JSON post:

 

 

  • {
  • "organizations":[],
  • "uuid":"2b50b3f00e04fc17912154a7b88f3359db2b1ae8",
  • "thread":{
  • "social":{
  • "gplus":{
  • "shares":0
  • },
  • "pinterest":{
  • "shares":1
  • },
  • "vk":{
  • "shares":0
  • },
  • "linkedin":{
  • "shares":0
  • },
  • "facebook":{
  • "likes":19,
  • "shares":63,
  • "comments":7
  • },
  • "stumbledupon":{
  • "shares":0
  • }
  • },
  • "site_full":"www.foxnews.com",
  • "main_image":"https://cf-images.us-east-1.prod.boltdns.net/v1/static/694940094001/abd7...",
  • "site_section":"http://feeds.foxnews.com/foxnews/latest",
  • "section_title":"FOX News",
  • "url":"https://www.foxnews.com/media/dr-siegel-on-coronavirus-i-think-is-a-whop...",
  • "country":"US",
  • "domain_rank":185,
  • "title":"Dr. Marc Siegel on coronavirus: 'I think it is a whopping amount of cases undiagnosed'",
  • "performance_score":0,
  • "site":"foxnews.com",
  • "participants_count":1,
  • "title_full":"",
  • "spam_score":0.0,
  • "site_type":"news",
  • "published":"2020-03-14T04:20:00.000+02:00",
  • "replies_count":0,
  • "uuid":"2b50b3f00e04fc17912154a7b88f3359db2b1ae8"
  • },
  • "author":"Victor Garcia",
  • "url":"https://www.foxnews.com/media/dr-siegel-on-coronavirus-i-think-is-a-whop...",
  • "ord_in_thread":0,
  • "title":"Dr. Marc Siegel on coronavirus: 'I think it is a whopping amount of cases undiagnosed'",
  • "locations":[],
  • "entities":{
  • "persons":[{
  • "name":"marc siegel",
  • "sentiment":"negative"
  • },{
  • "name":"siegel",
  • "sentiment":"none"
  • },{
  • "name":"tucker carlson",
  • "sentiment":"none"
  • },{
  • "name":"trump",
  • "sentiment":"none"
  • },{
  • "name":"trump",
  • "sentiment":"none"
  • }],
  • "locations":[{
  • "name":"us",
  • "sentiment":"none"
  • }],
  • "organizations":[{
  • "name":"fox news",
  • "sentiment":"negative"
  • }]
  • },
  • "highlightText":"",
  • "language":"english",
  • "persons":[],
  • "text":"US doctors report inability to get tests for coronavirus patients Reaction from Fox News medical correspondent Dr. Marc Siegel. Dr. Marc Siegel appeared on \" Tucker Carlson Tonight \" on Friday where he gave his assessment of the coronavirus pandemic in the aftermath of President Trump declaring a national emergency. \"There's many thousands of cases that have not been diagnosed, possibly because they're mild, but it's not too late to test because we don't have another system we can work with,\" Siegel said.\nTRUMP DECLARES NATIONAL EMERGENCY OVER CORONAVIRUS, ENLISTS PRIVATE SECTOR\nSiegel also spoke about the problems hospitals and labs are having, fearing they are exposing their workers to the virus.\n\"Doctors are being told you don't see these patients. Well, we don't know what to do with them then. And the only thing we have is a test, except you can't actually do the test because the lab, and I just found out this today... they're not going to do the tests,\" Siegel said. \"Tucker, even if they have the equipment, they don't want to put their lab technicians, in my opinion, in the line of fire and be subjected to possible coronavirus.\"\nThe solution, according to the Fox News medical contributor, is to do what South Korea and facilities in Nebraska are doing -- drive-thru testing facilities.\n\"You have to have people dressed up in personal protective equipment like we showed in Nebraska. They have to be doing [it] very carefully. And it's got to be done on a high volume basis anyway,\" Siegel said. \"It can't be contained anymore. But I'll tell you why I want it done.\"\nCLICK HERE TO GET THE FOX NEWS APP\nSiegel said although the virus has already spread, testing is vital to \"reassure people who don't have it\" and \"decrease the panic.\"\n\"We have to know who has this so we can protect the people most at risk, even if it's sustained throughout all communities,\" Siegel said. \"I think it is a whopping amount of cases undiagnosed. We still need to know who has it.\" Get all the stories you need-to-know from the most powerful name in news delivered first thing every morning to your inbox Arrives Weekdays",
  • "external_links":["https://www.google.com/url","https://google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=12&cad=rja&uac...","https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=12&cad=rja..."],
  • "published":"2020-03-14T04:20:00.000+02:00",
  • "crawled":"2020-03-14T04:31:41.175+02:00",
  • "highlightTitle":""
  • }

 

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This dataset includes CSV files that contain IDs and sentiment scores of the tweets related to the COVID-19 pandemic. The real-time Twitter feed is monitored for coronavirus-related tweets using 90+ different keywords and hashtags that are commonly used while referencing the pandemic. The oldest tweets in this dataset date back to October 01, 2019. This dataset has been wholly re-designed on March 20, 2020, to comply with the content redistribution policy set by Twitter.

Instructions: 

Each CSV file contains a list of tweet IDs. You can use these tweet IDs to download fresh data from Twitter (read this article: hydrating tweet IDs). To make it easy for the NLP researchers to get access to the sentiment analysis of each collected tweet, the sentiment score computed by TextBlob has been appended as the second column. To hydrate the tweet IDs, you can use applications such as Hydrator (available for OS X, Windows and Linux) or twarc (python library).

Getting the CSV files of this dataset ready for hydrating the tweet IDs:

import pandas as pd

dataframe=pd.read_csv("corona_tweets_10.csv", header=None)

dataframe=dataframe[0]

dataframe.to_csv("ready_corona_tweets_10.csv", index=False, header=None)

The above example code takes in the original CSV file (i.e., corona_tweets_10.csv) from this dataset and exports just the tweet ID column to a new CSV file (i.e., ready_corona_tweets_10.csv). The newly created CSV file can now be consumed by the Hydrator application for hydrating the tweet IDs. To export the tweet ID column into a TXT file, just replace ".csv" with ".txt" in the to_csv function (last line) of the above example code.

If you are not comfortable with Python and pandas, you can upload these CSV files to your Google Drive and use Google Sheets to delete the second column. Once finished with the deletion, download the edited CSV files: File > Download > Comma-separated values (.csv, current sheet). These downloaded CSV files are now ready to be used with the Hydrator app for hydrating the tweet IDs.

Playing around with 'tweet ID' and 'date & time'

In this dataset, tweet IDs are listed in different CSV files based on their creation dates. However, if you are interested in hydrating the IDs that fall between a specific time interval, you can convert a tweet ID to date & time (tweet ID > time epoch > human-readable date & time). Yes, you read it correctly; Twitter has a timestamp placed in tweet ID. You can also convert a time epoch to tweet ID. This way, you can easily select a list of tweet IDs from this dataset that fall under your preferred time frame.

Converting tweet ID to date & time

import time

tweet_id = ...

shifted_id = tweet_id >> 22 #applying right shift operator to the tweet ID

timestamp = shifted_id + 1288834974657 

data_time = time.ctime(timestamp/1000)

Converting date & time to tweet ID

milisecond epoch = ... #convert the preferred date & time to ms epoch

epoch = milisecond epoch - 1288834974657

tweet_id = epoch << 22 #applying left shift operator

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