  The purpose of this study is to clarify what kind of news is easily retweeted
and what kind of news is easily Liked. We believe these actions, retweeting and
Liking, have different meanings for users. Understanding this difference is
important for understanding people's interest in Twitter. To analyze the
difference between retweets (RT) and Likes on Twitter in detail, we focus on
word appearances in news titles. First, we calculate basic statistics and
confirm that tweets containing news URLs have different RT and Like tendencies
compared to other tweets. Next, we compared RTs and Likes for each category and
confirmed that the tendency of categories is different. Therefore, we propose
metrics for clarifying the differences in each action for each category used in
the $\chi$-square test in order to perform an analysis focusing on the topic.
The proposed metrics are more useful than simple counts and TF-IDF for
extracting meaningful words to understand the difference between RTs and Likes.
We analyzed each category using the proposed metrics and quantitatively
confirmed that the difference in the role of retweeting and Liking appeared in
the content depending on the category. Moreover, by aggregating tweets
chronologically, the results showed the trend of RT and Like as a list of words
and clarified how the characteristic words of each week were related to current
events for retweeting and Liking.
