631 research outputs found
Animation author in Showa Seo Mitsuo
No full textFurthermore, it is also surprising that not much studying has been done on Seo Mitsuo either, who created about 25 pieces of work during the period of 1932 and 1949 through a method known as “Sell Animation.” The purpose of this study is to understand Kenjo Masaoka, a genius of Sell Animation, and analyze his works in order to identify the nature of those works.There are five main points in conclusion: first, of division of labor was developed more by use of a cell, and that a big hint was given to a division system of an after Japan animation co. The thing in which two could express a movement of the character which makes a story stand out freely using a cell. Such as applying to a movie cartoon three of taking a picture, various methods are tried, consequently, the thing which improved the quality of a movie cartoon. I kept studying four music methods, and that musical visualization was advanced. Five kept educating the posterity represented by Mitsuyo Seo and others, and that their ability was improved
Japanese "Abe" Tweets from 2019-02-10 to 2020-10-07 (15,407,811 tweets and 114,231,250 retweets)
No full textAbstract (our paper)
To examine conservative–liberal differences in the extent to which partisan tweets reach less partisan moderate users in a nonwestern context, we analyzed a network of retweets about former Japanese Prime Minister Shinzo Abe. The analyses consistently demonstrated that partisan tweets originating from the conservative cluster reach a wider range of moderate users than those from the liberal cluster. Network analyses revealed that while the conservative and the liberal clusters’ internal structures were similar, the conservative cluster reciprocated the follows from moderate accounts at a higher rate than the liberal cluster. In addition, moderate accounts reciprocated the conservative cluster’s following at a higher rate than they did for the liberal cluster. The analysis of tweet content showed no difference in the frequency of hashtag use between conservatives and liberals, but there were differences in the use of emotion words and linguistic expressions. In particular, emotion words related to the propagation of messages, such as those expressing “dislike”, were used more frequently by conservatives, while the use of adjectives by conservatives was closer to that of moderate users, indicating that conservative tweets are more palatable for moderate users than liberal tweets.
Data
Abe.tsv.gz:
The first column is the tweet id, the second column is the tweet id of the retweet source, and the third column is the date and time (JST) when the tweet was posted.
This data was collected by giving the query "安倍 OR アベ" to the Twitter Search API. Therefore, most of the tweets are Japanese tweets. The second column is empty if the tweet is not a retweet.
Publication
This data set was created for our study. If you make use of this data set, please cite:
Mitsuo Yoshida, Takeshi Sakaki, Tetsuro Kobayashi, Fujio Toriumi. Japanese conservative messages propagate to moderate users better than their liberal counterparts on Twitter. Scientific Reports. vol.11, article no.19224, 2021.
https://doi.org/10.1038/s41598-021-98349-
Synthetic Inorganic Ion-exchange Materials. XXVI. Ion-exchange Properties of Crystalline Antimonic(V) Acid towards Noble Metals in Nitric Acid Media
No full textNotes on the Peerage of the Ts'ao-Wei Dynasty
No full textWith a view to clarifying a few interesting points on the peerage system of the Wei of the Three Dynasties period, firstly the author takes up the process of formation of the Ts'ao-Wei peerage, where it consisted of the five-grade peerage of the Chou period, the lieh-hou 列侯 and khuan-nei-hou 關内侯 titles after the Ch'in-Han system, and the peerage created by Wei itself. Secondly, the author discusses the size of the lieh-hou and khuan-nei-hou fiefs in terms of household and their inner structure. Lastly, the author points out that heir apparency was widened under the Wei, though the "inheritance by real son" principle of the Han period was still in practice. In view of the fact that fiefs were sometimes divided even in the life-time of lord the author relates the Wei peerage to its noble lineage system
Google Trends and Wikipedia Page Views
No full text<p><strong>Abstract</strong> (our paper)</p>
<p>The frequency of a web search keyword generally reflects the degree of public interest in a particular subject matter. Search logs are therefore useful resources for trend analysis. However, access to search logs is typically restricted to search engine providers. In this paper, we investigate whether search frequency can be estimated from a different resource such as Wikipedia page views of open data. We found frequently searched keywords to have remarkably high correlations with Wikipedia page views. This suggests that Wikipedia page views can be an effective tool for determining popular global web search trends.</p>
<p><strong>Data</strong></p>
<p>personal-name.txt.gz:<br>
The first column is the Wikipedia article id, the second column is the search keyword, the third column is the Wikipedia article title, and the fourth column is the total of page views from 2008 to 2014.</p>
<p>personal-name_data_google-trends.txt.gz, personal-name_data_wikipedia.txt.gz:<br>
The first column is the period to be collected, the second column is the source (Google or Wikipedia), the third column is the Wikipedia article id, the fourth column is the search keyword, the fifth column is the date, and the sixth column is the value of search trend or page view.</p>
<p><strong>Publication</strong></p>
<p>This data set was created for our study. If you make use of this data set, please cite:<br>
Mitsuo Yoshida, Yuki Arase, Takaaki Tsunoda, Mikio Yamamoto. Wikipedia Page View Reflects Web Search Trend. <em>Proceedings of the 2015 ACM Web Science Conference (WebSci '15)</em>. no.65, pp.1-2, 2015.<br>
http://dx.doi.org/10.1145/2786451.2786495<br>
http://arxiv.org/abs/1509.02218 (author-created version)</p>
<p><strong>Note</strong></p>
<p>The raw data of Wikipedia page views is available in the following page.<br>
http://dumps.wikimedia.org/other/pagecounts-raw/</p>
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