Search

The Olympic Games are a typical media event and are seen as a festive occasion that monopolizes people's attention through the mass media. The Games and their media coverage have a predetermined schedule that enhances the nation's sense of unity by placing a temporary truce on political conflicts. Governments, especially those of Olympic host countries, tend to take advantage of this effect to garner support for their own policies. However, the effects of such media events may be weakening owing to changes in the media environment and increasing political polarization. Examining the 2020 Tokyo Olympic Games, this case study analyzes a large amount of Twitter data to probe Japanese social media users' attitudes toward the Olympic Games and the relationship of these attitudinal changes with their attitudes toward the political leadership of the prime minister. The results showed that previously negative attitudes toward the Olympic Games improved as people enjoyed the event. However, this positive shift did not appear to be associated with their attitudes toward the prime minister. Users' political predispositions strongly determined their attitudes toward the Olympic Games, indicating that the Olympic Games as a media event had limited implications for support for the administration. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Twitter has received much attention recently. An important characteristic of Twitter is its real-time nature. We investigate the real-time interaction of events such as earthquakes in Twitter and propose an algorithm to monitor tweets and to detect a target event. To detect a target event, we devise a classifier of tweets based on features such as the keywords in a tweet, the number of words, and their context. Subsequently, we produce a probabilistic spatiotemporal model for the target event that can find the center of the event location. We regard each Twitter user as a sensor and apply particle filtering, which are widely used for location estimation. The particle filter works better than other comparable methods for estimating the locations of target events. As an application, we develop an earthquake reporting system for use in Japan. Because of the numerous earthquakes and the large number of Twitter users throughout the country, we can detect an earthquake with high probability (93 percent of earthquakes of Japan Meteorological Agency (JMA) seismic intensity scale 3 or more are detected) merely by monitoring tweets. Our system detects earthquakes promptly and notification is delivered much faster than JMA broadcast announcements. [ABSTRACT FROM AUTHOR]

Abstract: Levels of acyl-hydrolase (EC 3.1.1.26) activity toward monogalactosyldiacylglycerol (MGDG) varied greatly not only in leaves of 12 plant species but also in those of 11 cultivars of kidney bean (Phaseolus vulgaris L.). The activity was detected in soluble and particulate fractions from kidney bean leaves, and the specific activity in both fractions was higher in young premature leaves than in the old in Koshu Shakugosun, a cultivar exhibiting the highest specific activity among kidney bean plants tested. The enzyme was purified 868-fold with a yield of 8.2% from the particulate fractions of leaf homogenate of this cultivar. The purified enzyme showed a single band on native polyacrylamide gel electrophoresis and a native molecular mass of 74kDa. The enzyme had broad substrate specificity toward classes of glycolipids, phospholipids, and monoacylglycerol, but was inactive to triacylglycerol, indicating that the enzyme belongs to non-specific lipid acyl-hydrolases. Distinct from other lipid acyl-hydrolases previously reported, however, the enzyme showed preferential hydrolysis at sn-1 position of MGDG. Antiserum prepared against the purified enzyme completely inhibited not only the purified enzyme activity but also the activity in the soluble fraction of leaf homogenate. Exposure to ozone, a stress to stimulate endogenous acyl hydrolysis of MGDG, of kidney bean cultivars with different acyl-hydrolase activity resulted in essentially the same changes in leaf lipids of all cultivars. [Copyright &y& Elsevier]

Despite the intensive study of the viral spread of fake news in political echo chambers (ECs) on social networking services (SNSs), little is known regarding the underlying structure of the daily information spread in these ECs. Moreover, the effect of SNSs on opinion polarisation is still unclear in terms of pluralistic information access or selective exposure to opinions in an SNS. In this study, we confirmed the steady, highly independent nature of left- and right-leaning ECs, both of which are composed of approximately 250,000 users, from a year-long reply/retweet network of 42 million Japanese Twitter users. We found that both communities have similarly efficient information spreading networks with densely connected and core-periphery structures. Core nodes resonate in the early stages of information cascades, and unilaterally transmit information to peripheral nodes. Each EC has resonant core users who amplify and steadily spread information to a quarter of a million users. In addition, we confirmed the existence of extremely aggressive users of ECs who co-reply/retweet each other. The connection between these users and top influencers suggests that the extreme opinions of the former group affect the entire community through the top influencers. [ABSTRACT FROM AUTHOR]

Burst phenomena are caused by such social events as flaming on the internet, elections, and natural disasters. To understand people's thoughts and feelings, we must classify their opinions from burst phenomena. Therefore, classification methods that categorize tweets are critical. However, since most classification methods focus on text mining, they cannot classify tweets by topics because each tweet has poor linguistic similarities. We used a non-text-based method proposed by Baba et al. that groups tweets by topics, even if they have poor linguistic similarities, and verified its validity by comparing it with a text-based method in two different evaluations: full data and sampled data. In the full data evaluation part, we did a questionnaire survey and validated the suitability of the topic clusters created by both classification methods using our full dataset. In the sampled data evaluation part, we focused on the robustness of each method against data reduction. Since collecting the whole data of burst phenomena is very costly due to the vast amounts of available social media data, robustness against data reduction is an important index to evaluate classification methods. After these evaluations, we found that the non-text-based method more effectively classified tweets than the text-based method. [ABSTRACT FROM AUTHOR]

Abstract: The major pharmacological ingredient in tobacco smoke is nicotine, a mild stimulant known to alter brain electrical activity. The objective of this study was to determine if tobacco smoking in humans produces localized or widespread neocortical dominant alpha electroencephalographic (EEG) frequency increases consistent with nicotine stimulation of the brainstem activating system in animals. Twenty-two male volunteer non-deprived tobacco smokers were studied. They were asked not to smoke for at least 1h before the experiment in mid-morning as part of their usual smoking schedule. In the laboratory, they sham smoked and then smoked their favorite tobacco cigarette. Two experimental sessions (#1 and #2) were conducted, separated by a one to two month interval. In both sessions, there were minor statistically significant increases in the dominant alpha frequencies after sham smoking. In both sessions, after the subjects smoked a favorite tobacco cigarette there was a significant generalized increase in dominant alpha EEG frequencies in most scalp recording sites. This study demonstrates that tobacco smoking produces widespread bilateral neocortical increases in dominant alpha EEG frequencies consistent with the stimulant effects of nicotine on the brainstem reticular activating system. [Copyright &y& Elsevier]