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星巴克 VS 央视:愤怒的情绪最容易在微博上传播

2017-09-20 5页 doc 20KB 15阅读

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星巴克 VS 央视:愤怒的情绪最容易在微博上传播星巴克 VS 央视:愤怒的情绪最容易在微博上传播 北京航空航天大学软件开发环境国家重点实验室的先进网络分析研究小组(Group of Advanced Network Analysis,GANA)通过对微博的情感分类和波动分析,研究各种情绪 在社交网络上的传播机制。结果发现:愤怒情绪的相关性最大。也就是说,如果你的微博 好友发了一条泄愤的微博,你也更容易跟着愤怒起来。这表明,愤怒情绪更易在社交网络 中传播。 Advanced network State Key Laboratory of Beihang Universi...
星巴克 VS 央视:愤怒的情绪最容易在微博上传播
星巴克 VS 央视:愤怒的情绪最容易在微博上传播 北京航空航天大学软件开发环境国家重点实验室的先进网络分析研究小组(Group of Advanced Network Analysis,GANA)通过对微博的情感分类和波动分析,研究各种情绪 在社交网络上的传播机制。结果发现:愤怒情绪的相关性最大。也就是说,如果你的微博 好友发了一条泄愤的微博,你也更容易跟着愤怒起来。这明,愤怒情绪更易在社交网络 中传播。 Advanced network State Key Laboratory of Beihang University software development environment analysis research group (Group of Advanced Network Analysis, GANA) through the emotion classification and fluctuation analysis of micro-blog, communication mechanism of emotions in social networks. Results: the anger of the maximum correlation. That is to say, if you micro-blog friend sent a micro-blog anger, you are more likely to follow in anger. This shows, angry more easily spread in a social network. GANA选取了2010年4月至9月期间新浪微博上的数据构建研究所需的交互网络,这些 数据包含了用爬虫抓取的近7000万条微博和20万个活跃用户的个人数据。“与Facebook 等社交性极强的网站不同,一般认为新浪微博这类Twitter式的社交服务中,关注关系并不 能表征可信的社交关系,而更多的是信息媒介。”GANA研究人员对果壳网说:“但讨论情 绪的影响,我们需要基于可靠的强社交关系来开展研究,因此我们依靠用户之间是否发生 过„@?或转发等互动来确定社交关系。” GANA selected during the period from 2010 April to September micro-blog construction sina on data exchange network for the study, these data include the crawler nearly 70000000 micro-blog and 200000 active users of personal data. "Unlike Facebook social strong website, Sina micro-blog generally believed that this kind of Twitter type social services, pay attention to relationship does not characterize the credible social relationships, and more is the information media." The GANA researchers on the shell network said: "but the discussion of emotional impact, we need reliable and strong social relationships based on research, so we rely on users' @ 'or any forwarding interaction to determine social relations." 研究人员认为,仅当实验期间两个用户之间发生过至少30次互动时,才能认为他们之间 存在可信的社交连接。基于这些社交联系,他们构建出了一个可靠的微博社交网络,并且 将其中的各种情绪细分为愤怒、喜悦、低落和厌恶四种,最终发现愤怒情绪的相关性甚至 超过了喜悦,而低落情绪的相关性则出乎意料的小。 The researchers believe that, only when the between experiment during two occurred at least 30 times the user interaction, to think there are credible social connection between them. Based on these social contact, they build a reliable micro-blog social networks, and various emotions subdivision the anger, joy, disgust and low four, finally found a correlation between anger and even more than joy, but the correlation between low mood is the anticipation of small. 在解释愤怒情绪出人意料的高相关性时,研究人员分析了网络中转发的(仅考虑转发是为 了去除外部其他媒体的影响)愤怒微博,利用话题模型和关键字抽取等方法,发现有两类 事件似乎更容易引发愤怒情绪:一类是中国与外国的冲突,例如美韩两国在黄海举行的联 合军演;另一类则是国内的社会热点话题,例如食品安全、官员腐败等。 In the interpretation of the high correlation of anger beyond all expectations, the researchers analyzed the forwarding www.meiguoqianggeng.com network (only consider forwarding is to affect the removal of other external media micro-blog) angry, the topic model and keyword extraction method, and found that two types of events seem to be more prone to anger: one is the conflict between China and foreign countries, for example, the two countries held a joint military drill in the Yellow Sea; another is the hot topic in society in China, such as food security, official corruption, etc.. GANA告诉果壳网:“所谓情绪的传播,本质仍然是信息的传播,但情绪是信息本身的一类 属性,而这类属性会在某些情况下(如愤怒)加速信息本身的流动,从而使其在网络中广 泛的扩散并形成公共话题或者网络事件。” GANA told the shell network: "the so-called emotional communication, essence is the dissemination of information, but the mood is a kind of attribute information itself, and this kind of property in some cases (such as anger) accelerated information flow, thus the network wide spread and form public topic or network events." 至于这一研究成果的应用前景,GANA的研究人员表示,“目前的发现可能有助于网络营销 策略或调查互联网事件快速传播背后的原因。”实际上,他们已经做了一些关于利用情 绪异常来进行互联网事件监测或发现的工作,还设计了一款包含情感维度的搜索引擎(这是 一个名为“心情搜索”的搜索引擎,可以获知大众对待被搜索话题的情感随时间的变化,还 可获知大众对该话题的主流看法和讨论)。 As for the application of the results of this study, GANA researchers said, "the present findings may contribute to the network marketing strategy design or an Internet events spread quickly behind." In fact, they have done something about the use of emotional disorders to Internet event monitoring or find work, also designed a affective search engine (this is a "mood search" search engine, can be informed public to search the subject emotion changes over time, still can informed the public on the subject of the mainstream view and discussion). “我们下一步会基于情绪的相关性,提出更细致的描述用户间情绪影响的动力学模型,讨论 用户间情绪影响的内在机制和传播动力学。”GANA称:“我们现在解决了一些基本问题, 即不同情绪的相关性不同,、且局部结构会对情绪相关性有所增强。但一些更深入的问 题,如情绪影响的内在机制、如何量化情绪对信息传播的加速等,仍需要进一步的工作。” "Our next step is based on the dynamic model of emotional relevance, proposed affects mood more detailed description between users, discusses the inherent mechanism and propagation dynamics affect mood among users." GANA said: "we solve some basic problems now, namely correlation of www.szking.net different mood, different, and local structure will be enhanced on the emotional relationship. But some deeper problems, such as how the internal mechanism, the emotional impact of the quantification of emotion on information dissemination acceleration, further work is still needed."
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