Microblogging Behavior on Sina Weibo and Twitter 21.2% entities 82.7%/17.3%65.6%/34.4% Organization 78.5%/21.3% 70.1%/29.9% Person 828%/172% 657%/34.3% Table 5. Sentiment expressed in (i)overall posts Fig 4. The ration of positive posts and (i)posts that mention certain types of topics on two microblogging services positive or negative. On Sina Weibo the portion of positive posts(78.8%)is clearly higher than on Twitter(70.5%). In Fig 4 we plot the ratio of positive posts with respect to all posts, which either have a positive or negative sentiment for individual users: 92.5% of the users publish more positive messages than negative ones on Sina Weibo in comparison to 86.4% for the Twitter users On Sina weibo. we also discover a considerable fraction of users for whom the non- neutral posts are always positive(8.0%)or always negative(5.6%) In Table 5 we moreover analyze the sentiment revealed in the microposts that mention certain types of entities. Again, the proportion of positive posts exceeds the proportion of negative posts clearly and Sina Weibo users tend to be more positive towards mentioned entities than Twitter users. Interestingly, whenever locations or persons are mentioned in Sina Weibo messages then the likelihood that the post is positive increases on Sina Weibo(from 78.8% to 82.7% and 82.8% respectively)while on Twitter the opposite can be observed(decrease from 70.5% to 65.6% and 65. 7% respectively) Findings Regarding the research questions RQ7 and rQ8 about the sentiment hat users express in their microposts, we conclude the following: F7: We observe that on both platforms there are significantly more positive posts than negative ones. Moreover, users on Sina Weibo have a stronger tendency to publish positive messages than Twitter users. In fact, the prob- ability for positive messages is 11.8% higher on Sina Weibo than on Twitter F8: The sentiment that is expressed in microposts correlates with the type of concepts that are mentioned in the posts On Sina Weibo posts that mention locations or persons are more likely to be positive than posts containin organizations. While on Twitter, the opposite can be observed: people talk more positively about organizations than about persons or locations. 4.5 Analysis of Temporal Behavior Results In Table 6 we first compare the posting behavior of users between working days and weekend days by calculating the ratio between the average number of posts per day published during the weekends(Saturday-Sunday)and the one during the week(Monday-Friday). For Sina Weibo this ratio is 1. 19 which means that Sina Weibo user publish, on average, 19% more messages per day on the weekend than they do during the week. On the other hand, the users on Twitter publish, on average, 11% less posts during the weekend. Therefore it seems that microblogging in China has not penetrated the daily(possibly work-related) routines as strongly as it does in Western countriesMicroblogging Behavior on Sina Weibo and Twitter 9 type of proportion of positive/negative posts posts Weibo Twitter Overall posts 78.8%/21.2% 70.5%/29.5% posts that mention certain types of entities: Location 82.7%/17.3% 65.6%/34.4% Organization 78.5%/21.5% 70.1%/29.9% Person 82.8%/17.2% 65.7%/34.3% Table 5. Sentiment expressed in (i) overall posts and (ii) posts that mention certain types of topics 0% 20% 40% 60% 80% 100% users 0% 20% 40% 60% 80％ 100% ratio of positve posts Weibo Twitter more negative posts more positive posts Fig. 4. The ration of positive posts on two microblogging services positive or negative. On Sina Weibo the portion of positive posts (78.8%) is clearly higher than on Twitter (70.5%). In Fig. 4 we plot the ratio of positive posts with respect to all posts, which either have a positive or negative sentiment, for individual users: 92.5% of the users publish more positive messages than negative ones on Sina Weibo in comparison to 86.4% for the Twitter users. On Sina Weibo, we also discover a considerable fraction of users for whom the non￾neutral posts are always positive (8.0%) or always negative (5.6%). In Table 5 we moreover analyze the sentiment revealed in the microposts that mention certain types of entities. Again, the proportion of positive posts exceeds the proportion of negative posts clearly and Sina Weibo users tend to be more positive towards mentioned entities than Twitter users. Interestingly, whenever locations or persons are mentioned in Sina Weibo messages then the likelihood that the post is positive increases on Sina Weibo (from 78.8% to 82.7% and 82.8% respectively) while on Twitter the opposite can be observed (decrease from 70.5% to 65.6% and 65.7% respectively). Findings Regarding the research questions RQ7 and RQ8 about the sentiment that users express in their microposts, we conclude the following: – F7: We observe that on both platforms there are significantly more positive posts than negative ones. Moreover, users on Sina Weibo have a stronger tendency to publish positive messages than Twitter users. In fact, the prob￾ability for positive messages is 11.8% higher on Sina Weibo than on Twitter. – F8: The sentiment that is expressed in microposts correlates with the type of concepts that are mentioned in the posts. On Sina Weibo posts that mention locations or persons are more likely to be positive than posts containing organizations. While on Twitter, the opposite can be observed: people talk more positively about organizations than about persons or locations. 4.5 Analysis of Temporal Behavior Results In Table 6 we first compare the posting behavior of users between working days and weekend days by calculating the ratio between the average number of posts per day published during the weekends (Saturday-Sunday) and the one during the week (Monday-Friday). For Sina Weibo this ratio is 1.19, which means that Sina Weibo user publish, on average, 19% more messages per day on the weekend than they do during the week. On the other hand, the users on Twitter publish, on average, 11% less posts during the weekend. Therefore, it seems that microblogging in China has not penetrated the daily (possibly work-related) routines as strongly as it does in Western countries