香山“长庆”有遗篇——试论《长恨歌》与《圆圆曲》的黍离之感

梅村体是长庆体的变格,但其中都充满着浓烈的黍离麦秀之感,所不同者在于一为乱世之音,一为亡国之音.诗人感伤兴寄,作垂戒之用.     

Socially organized sentiments: Exploring the link between religious density and protest mobilization, 1960–1995

Extensive research has shown individual religiosity to have an impact upon U.S. protest participation. But very little work has examined the role of religious density in a community on the likelihood of protest mobilization. Our research links the religious density across 62 counties in New York State to various protest mobilization issues during the period of 1960–1995. In this research, we develop a theory of socially organized sentiments to examine religious influences on overall protest event mobilizations in local communities, a specific example of a more general theory that can link community structure to multiple forms of civic engagement. The impact of various religious traditions is assessed by using measures for the density of religious population per congregation of three religious traditions—Mainline Protestantism, Evangelical Protestantism and Catholicism. The analysis also assesses the likelihood of mobilization concerning four specific issues—African-American civil rights, gender, anti-nuclear/peace, and anti-poverty movements.     

金融市场收益率方向预测模型研究———基于文本大数据方法

金融市场的发展关系着一国的经济命脉,而股票市场作为金融市场的重要组成部分,对其收益率的研究也一直都是学术界的热点。财经新闻常被认为蕴含着丰富的信息,其中所包含的情感信息作为影响投资者投资决策的重要因素之一,对股票收益率也具有一定的影响。故本文构建了适用于金融投资领域的财经新闻情感词典来对财经新闻进行文本分析,同时构造了新的预测模型:将财经新闻文本中所含的情感量化为情绪指数并与时变密度函数相结合,得到时变加权密度模型。并在此基础上以模型评分为权重组合多个预测模型构建出评分加权模型用于股票收益率预测。结果显示,加入情绪指数能有效提高模型预测能力,而评分加权模型的预测能力则在此基础上更进一步,在准确率以及评分规则上基本达到双重最优。     

How publics react to situational and renewing organizational responses across crises: Examining SCCT and DOR in social-mediated crises

The prevalence of social media among networked publics calls for more research regarding how organizations can conduct effective crisis communication on social networking sites. Based on the situational crisis communication theory (SCCT) and the discourse of renewal (DOR) theory, this study examined how social media publics’ sentiments were affected by situational and renewing organizational responses in various clusters of crises. Twitter data of six crises representing three crisis clusters varying in the responsibility attribution (i.e., ambiguous, accidental, and preventable) were collected. We conducted a content analysis on organizations’ official tweets during crises (N = 59) and sentiment analysis on publics’ replies on Twitter (N = 4,340). The results showed that publics’ positive sentiments toward organizations were affected by organizational crisis responses that included instructing information, sympathy, systemic organizational learning, and effective organizational rhetoric. We recommend that crisis managers express sympathy toward publics as well as organizational learning that prevents a crisis from happening again.     

和谐社会条件下的三元和谐英语教学

和谐是当今社会的主旋律之一。本文提出了三元和谐英语教学理念，分析了三元与英语教学之间的内在关系，对于英语教学的改革以及高校的和谐稳定具有一定的借鉴意义。     

辛稼轩咏物词的寄托

辛稼轩的咏物词具有独特的个性风神,他将身世经历,风神志意灌注于物象之上,通过情和物的结合,寄托了家国之思、政治愤慨、俊逸风神和闲适情怀。辛稼轩的咏物词同他的其他题材的作品共同陶写了英雄志意。     

Trading on Twitter: Using Social Media Sentiment to Predict Stock Returns

Decision making is often based on the rational assessment of information, but recent research shows that emotional sentiment also plays an important role, especially for investment decision making. Emotional sentiment about a firm's stock that spreads rapidly through social media is more likely to be incorporated quickly into stock prices (e.g., on the same trading day it was expressed), while sentiment that spreads slowly takes longer to be incorporated into stock prices and thus is more likely to predict stock prices on future days. We analyzed the cumulative sentiment (positive and negative) in 2.5 million Twitter postings about individual S&P 500 firms and compared this to the stock returns of those firms. Our results show that the sentiment in tweets about a specific firm from users with less than 171 followers (the median in our sample) had a significant impact on the stock's returns on the next trading day, the next 10 days, and the next 20 days. Interestingly, sentiment in tweets from users with fewer than 171 followers that were not retweeted had the greatest impact on future stock returns. A trading strategy based on these findings produced meaningful economic gains on the order of an 11–15% annual return.     

《边城》：和谐音符中的不和谐

《边城》是现代文学史上一个纯洁的小说文本,众多研究者对小说文本的分析往往注重其和谐性。但是在文本的重新阅读中,笔者发现《边城》文本其实也充满了不和谐,具体表现在翠翠身世的悲剧(翠翠父母爱情之悲剧)、大老之死、傩送和翠翠之爱和爷爷之死。正是这种不和谐音符使作品的意韵才更丰富,哀惋的牧歌情调才得以显现。     

利用亲情关系开展思想政治教育的理论基础

思想政治教育作为一门科学,与心理学、社会学、教育学、伦理学有着密切的联系。亲情关系是人类社会中最基本的人际关系,它与这些相关学科也有着不可分割的内在联系,是这些学科都不能忽视的研究领域之一。因此,利用亲情关系进行思想政治教育具有心理学、社会学、教育学、伦理学方面的理论基础。     

Tracking phantastic objects: A computer algorithmic investigation of narrative evolution in unstructured data sources

We develop social network and “relative sentiment shift” analysis techniques to study how financial narratives influence financial markets. First, we analyze Reuters News articles focusing on narratives about Fannie Mae. Second, we analyze Broadband and Energy narratives in the Enron Corporation email database. Combining datasets we show that phantastic object narratives can be detected and tracked as they develop and spread through networks to lead to a disconnect between narrative and underlying “reality”. The methods may be applicable to other text datasets to create early warnings.