Using the shaping filter to remove the effects of the bubble pulses of explosive charge, we obtained the impulse response function of the sea bottom. The result is quite satisfactory.
Minority opinions can be of crucial importance to the diversity, productivity, and harmony of a group, but are often left unat-tended and unheard. Previous methods that tried to enhance minority influence are usually ...Minority opinions can be of crucial importance to the diversity, productivity, and harmony of a group, but are often left unat-tended and unheard. Previous methods that tried to enhance minority influence are usually overly forceful and low on ecological validity. To overcome these pitfalls, we proposed a new intervention method called minority clustering and examined its effects with a social network experiment (N = 456). Minority clustering was implemented by increasing the network connections among participants with initial opinions that deviated from the mainstream opinion and forming an opinion cluster among these minor-ity members. Our results show that minority clustering significantly slowed down the rate at which minority members shifted toward majority opinions, thereby sustaining minority cohesion, and moved majority members closer to minority opinions, thus enhancing minority influence. An additional filter bubble intervention, through which all members of a network were exposed to neighbors with similar opinions to their own, further strengthened minority cohesion but weakened minority influence. Minority clustering is an unobtrusive intervention that does not need overt cooperations of network members and can be im-plemented easily in social media platforms. The working mechanisms of minority clustering and its effects on group opinion formation are further discussed.展开更多
Personalized recommender systems provide various personalized recommendations for different users through the analysis of their respective historical data.Currently,the problem of the“filter bubble”which has to do w...Personalized recommender systems provide various personalized recommendations for different users through the analysis of their respective historical data.Currently,the problem of the“filter bubble”which has to do with over-specialization persists.Serendipity(SRDP),one of the evaluation indicators,can provide users with unexpected and useful recommendations,and help to successfully mitigate the filter bubble problem,and enhance users’satisfaction levels and provide them with diverse recommendations.Since SRDP is highly subjective and challenging to study,only a few studies have focused on it in recent years.In this study,the research results on SRDP were summarized,the various definitions of SRDP and its applications were discussed,the specific SRDP calculation process from qualitative to quantitative perspectives was presented,the challenges and the development directions were outlined to provide a framework for further research.展开更多
文摘Using the shaping filter to remove the effects of the bubble pulses of explosive charge, we obtained the impulse response function of the sea bottom. The result is quite satisfactory.
基金supported by research grant of the National Natural Science Foundation of China awarded to Shenghua Luan(grant number 32171074).
文摘Minority opinions can be of crucial importance to the diversity, productivity, and harmony of a group, but are often left unat-tended and unheard. Previous methods that tried to enhance minority influence are usually overly forceful and low on ecological validity. To overcome these pitfalls, we proposed a new intervention method called minority clustering and examined its effects with a social network experiment (N = 456). Minority clustering was implemented by increasing the network connections among participants with initial opinions that deviated from the mainstream opinion and forming an opinion cluster among these minor-ity members. Our results show that minority clustering significantly slowed down the rate at which minority members shifted toward majority opinions, thereby sustaining minority cohesion, and moved majority members closer to minority opinions, thus enhancing minority influence. An additional filter bubble intervention, through which all members of a network were exposed to neighbors with similar opinions to their own, further strengthened minority cohesion but weakened minority influence. Minority clustering is an unobtrusive intervention that does not need overt cooperations of network members and can be im-plemented easily in social media platforms. The working mechanisms of minority clustering and its effects on group opinion formation are further discussed.
文摘Personalized recommender systems provide various personalized recommendations for different users through the analysis of their respective historical data.Currently,the problem of the“filter bubble”which has to do with over-specialization persists.Serendipity(SRDP),one of the evaluation indicators,can provide users with unexpected and useful recommendations,and help to successfully mitigate the filter bubble problem,and enhance users’satisfaction levels and provide them with diverse recommendations.Since SRDP is highly subjective and challenging to study,only a few studies have focused on it in recent years.In this study,the research results on SRDP were summarized,the various definitions of SRDP and its applications were discussed,the specific SRDP calculation process from qualitative to quantitative perspectives was presented,the challenges and the development directions were outlined to provide a framework for further research.
