Check and categorise 12,000 Dutch social media messages

Background We have 2 spreadsheets of social messages. We need a native Dutch speaker to check in total 12,000 messages, together with putting the correct values in the "human check" column. (Label the correct sentiment in this column, -1 is negative sentiment, 0 is neutral and +1 is positive sentiment. Instructions file: "nl_negative_aw1" Note: This spreadsheet meant to show all social messages with negative sentiment. 1. If the social message is supposed to be positive, put 1 in "human check" column ; if the social message is supposed to be neutral, put 0 in "human check" column, if the social message is negative, do nothing and move on to next message. 2. tag data in the "human check" column, for row 2-6001 file: "nl_positive_aw1" Note: This spreadsheet meant to show all social messages with positive sentiment. 1. If the social message is supposed to be negative, put -1 in "human check" column ; if the social message is supposed to be neutral, put 0 in "human check" column, if the social message is positive, do nothing and move on to next message. 2. tag data in the "human check" column, for row 2-6001 Pre-requirement *The freelancer must have his/her Twitter account and read and post messages regularly. The pre-requirement for this project is to work through 100 messages (50 from positive and 50 from negative), then email the results to us to check. Once we are happy with the quality of work done on the 100 messages, we will award the project. Our guideline 1. If the overall sentiment is positive then the labelling should be positive, we are trying to capture the overall sentiment and should avoid labelling with weight towards a small phrase within the message (good morning). 2. Spam and porn – we will usually rate 0 (neutral for spams) , and -1 if it’s a really nasty porn/filthy/vulgar comments.