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Crowdsourcing Workshift > Find work > Social media data cleaning

Job name

Social media data cleaning

Area Limitation
United States
Project Budget JPY
50,000 yen to 100,000 yen
Job type
Project
Open End

Requirements

1. Area

United States

2. Need Identity Verification

No

3. Skills

Other Data Entry

Description

Object: Identify and extract commercial comments in tweet posts.

Requirements:
The task does not require any specific analytical skills, but requires basic Excel skills.
The task requires you to read through the tweets posted by athletes and take memos when you find corporate/ product names in their tweet texts.

Data volume: 119,324 tweets
Method: See the example sheet attached
Identify commercial comments (including corporate name, product, champaign, university name) in the list of tweet posts (text colum) and extract commercial elements in the right columns.

Categories of the commercial elements:
I. Corporate
Example post: " Just joined the @Killerspin family! So excited :D"
Commercial element: "Killerspin" (table tennis equipment company)
Operation: Put "Killerspin" in the "corporate" column

II.product
Example post: "RT @TheSliceTweets: Hanging out at Duane Reade with @Bryanbros @Bryanbrothers and the @NestleNesquik Bunny! http://t.co/DkhUtrk0"
Commercial element: "NestleNesquik"
Operation: Put "Nesquik" in the "product" column

III.university(affiliation)
Example post: "A pic with the @Reds Rosie Red. She is now my 2nd favorite mascot behind of course Stanford's The Tree. http://t.co/Wynld4u8"
Commercial element: "Stanford"
Operation: Put "Stanford" in the "university" column

IV.champaign
Example post: "Yesterday we stopped by the USA House to see the @CitiEveryStep Footprint Wall. What a honor to be on there. http://t.co/oTetsolC"
Commercial element: "CitiEveryStep"
Operation: Put "CitiEveryStep" in the "campaign" column

V. Other
Other posts including commercial intention

*note: if there are several commercial elements in a post, extract all elements and put them into appropriate columns
Example post: "Nestle If all goes wrong at the Open at least we'll leave as the Nesquik ping pong champs. http://t.co/kMLQpTS0"
Operation: "Nestle" to "corporate" column, "Nesquik" to "product" column

if there are several commercial elements but in the same category in a post, extract all elements and put them into same category colums
Example post: "RT @asiance: @topspinmovie @ArielHsing hahah yeah! We're working on them!! Killerspin"
Operation: corporate:"asiance"(new line)"Killerspin" to the "corporate" column

Introduction by Client and Background of Job

I conduct research about social media marketing during Olympic games.

About Fee

  • Project Budget (tax included)

    Client Desired Fee 50,000 yen to 100,000 yen
  • Details of remuneration

    About 0.5 cents per tweet. About $600 total.
    Usually those commercial tweets appear only 5 out of 300 tweets. You can just read through non-commercial tweets without any tasks.

Posting Ends

2018-08-18

Desired Delivery Date

From hiring date 14 Days

Attachment

US2012-2016.xlsx file_downloaddownload

Delivery Format

excel

Criteria for Hiring

Prohibitions

Others

Client information

Identification: Verified
Authorized by Workshift
Publication Date 2018-08-11 04:46
Applications Proposal number: 29  
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