Description

The final step of this section is about the sentiment analysis of the 200 news we chose. in the diagram, the value on the vertical axis is the text emotional polarity (-1 totally negative, 0 neutral, 1 totally positive.). The value on the horizontal axis represent the times that each polarity appears.

In the diagram, we can see most of the reports on both sides all have a negative attitude about climate change. but in another hand, china have more positive news than United states has.

Protocol

1.put the 200 news in google sheets, one for each row.

2.Use the Text Mining add-on (Dandelion API) to detect sentiment and emotions in the texts. The result we got is the text emotional polarity (-1 totally negative, 0 neutral, 1 totally positive.)

3.Use Excle to truncate the emotional polarity value to an integer, and next count the quantity of each integer value.

Data

Data source: Baidu, Google