Headline analyses

*Abstract

             

              For this week’s experiment, I did continuously research on the methods of “Sentimental Analysis” for news headlines. Previously, I found two software which can analyze sentences. They are “Corenlp” and “Text analysis (Google sheet’s add-on)”. Therefore, this time, I tried to find the way that increases the credibility of the results of Sentimental analysis using them.

*Method

              As you instructed in the last meeting, I compared the three results of “my reaction”, “Corenlp” and “Text Analysis” to calculate the credible sentimental trend. Then, I also searched for the news headlines which all three criteria regarded as the same category (Positive, Negative and Neutral).

*Result (P: Positive / N: Negative / L: Neutral)

News headlines	My Reaction	Corenlp	Text Analysis	Mean
UK net migration hits record high.	L	P	L	L
Who will be banned under Trump's immigration plan?	L	L	L	L
Eastern European workers in UK pass one million.	N	L	L	L
Australia's immigration minister accuses asylum seekers of lying.	N	N	N	N
Germany's AfD leader wants failed asylum seekers housed on islands.	N	N	N	N
Changing attitudes of a German city.	L	L	N	L
Anti-Islam group storms Anglican church in Australia.	N	L	L	L

*Conclusion

All in all, the result of the experiment was useful in that I could find some possibility that there might be some ways to evaluate the sentimental analysis for news headline using those software. However, I found that there were also many drawbacks to fix in order to get credible information. For example, the reliability of the assessment is still not so strong. It would be necessary for me to learn from the similar themes to make my research method more academically suitable.