Online reviews are considered of an important indicator for users to decide on the activity they wish to do, whether it is watching a movie, going to a restaurant, or buying a product. It also serves businesses as it ...Online reviews are considered of an important indicator for users to decide on the activity they wish to do, whether it is watching a movie, going to a restaurant, or buying a product. It also serves businesses as it keeps tracking user feedback. The sheer volume of online reviews makes it difficult for a human to process and extract all significant information to make purchasing choices. As a result, there has been a trend toward systems that can automatically summarize opinions from a set of reviews. In this paper, we present a hybrid algorithm that combines an auto-summarization algorithm with a sentiment analysis (SA) algorithm, to offer a personalized user experiences and to solve the semantic-pragmatic gap. The algorithm consists of six steps that start with the original text document and generate a summary of that text by choosing the N most relevant sentences in the text. The tagged texts are then processed and then passed to a Naive Bayesian classifier along with their tags as training data. The raw data used in this paper belong to the tagged corpus positive and negative processed movie reviews introduced in [1]. The measures that are used to gauge the performance of the SA and classification algorithm for all test cases consist of accuracy, recall, and precision. We describe in details both the aspect of extraction and sentiment detection modules of our system.展开更多
【目的】研究中国科技期刊国际影响力提升计划D类项目2013-2018年资助期刊被Web of Science(Wo S)数据库收录情况,考察D类项目资助期刊的发展成效,为世界一流期刊的建设提供参考。【方法】利用Wo S数据库,统计分析SCIE/SSCI收录D类项目...【目的】研究中国科技期刊国际影响力提升计划D类项目2013-2018年资助期刊被Web of Science(Wo S)数据库收录情况,考察D类项目资助期刊的发展成效,为世界一流期刊的建设提供参考。【方法】利用Wo S数据库,统计分析SCIE/SSCI收录D类项目资助期刊的学科分布和文献计量指标,评价D类项目资助期刊对SCI空白学科和优势学科的填补作用。【结果】D类项目资助期刊中有21种期刊被SCIE/SSCI收录,47.6%的收录期刊进入Q1区,5种期刊填补了SCI学科空白,16种期刊有效增补了优势/前沿学科。【结论】D类项目资助培育了一批优质期刊,成果显著,21种已被SCIE/SSCI收录的期刊代表了优势/前沿学科,或填补了学科空白,对世界一流期刊建设起到了推动作用。展开更多
Web 2.0的兴起,赋予网民多种形式参与政治知识建构的机会。知识生产的不平等开始取代知识获取的不平等,成为数字化时代研究社会不平等的关键面向。本文对美国社会的网络知识生产进行了实证探讨。通过对一份全国性电话调查数据的分析,研...Web 2.0的兴起,赋予网民多种形式参与政治知识建构的机会。知识生产的不平等开始取代知识获取的不平等,成为数字化时代研究社会不平等的关键面向。本文对美国社会的网络知识生产进行了实证探讨。通过对一份全国性电话调查数据的分析,研究发现受教育程度高的个体倾向于以文字的形式书写政治博客,而受教育程度低的和年轻个体更热衷于以图片和视频的形式发布博客。同时,年轻用户比老年用户更喜欢就政治博客发表评论。本研究发现,在所有形式的知识生产中,只有评论和图片与政治参与相关。这意味着新媒体技术具有某种强化边缘、赋权弱势的民主潜力。至于政治参与,研究结果可谓喜忧参半。这表明,虽然社会经济地位较高者仍然在网上保持一定优势,社会经济地位较低者也能够从网络的互动和融合属性中获得一定的益处。因此,网络知识生产一方面折射出美国真实社会的结构性不平等,另一方面也为重构政治传播的格局和强化公共领域的参与和互动元素创造了一些新的机会。展开更多
文摘Online reviews are considered of an important indicator for users to decide on the activity they wish to do, whether it is watching a movie, going to a restaurant, or buying a product. It also serves businesses as it keeps tracking user feedback. The sheer volume of online reviews makes it difficult for a human to process and extract all significant information to make purchasing choices. As a result, there has been a trend toward systems that can automatically summarize opinions from a set of reviews. In this paper, we present a hybrid algorithm that combines an auto-summarization algorithm with a sentiment analysis (SA) algorithm, to offer a personalized user experiences and to solve the semantic-pragmatic gap. The algorithm consists of six steps that start with the original text document and generate a summary of that text by choosing the N most relevant sentences in the text. The tagged texts are then processed and then passed to a Naive Bayesian classifier along with their tags as training data. The raw data used in this paper belong to the tagged corpus positive and negative processed movie reviews introduced in [1]. The measures that are used to gauge the performance of the SA and classification algorithm for all test cases consist of accuracy, recall, and precision. We describe in details both the aspect of extraction and sentiment detection modules of our system.
文摘【目的】研究中国科技期刊国际影响力提升计划D类项目2013-2018年资助期刊被Web of Science(Wo S)数据库收录情况,考察D类项目资助期刊的发展成效,为世界一流期刊的建设提供参考。【方法】利用Wo S数据库,统计分析SCIE/SSCI收录D类项目资助期刊的学科分布和文献计量指标,评价D类项目资助期刊对SCI空白学科和优势学科的填补作用。【结果】D类项目资助期刊中有21种期刊被SCIE/SSCI收录,47.6%的收录期刊进入Q1区,5种期刊填补了SCI学科空白,16种期刊有效增补了优势/前沿学科。【结论】D类项目资助培育了一批优质期刊,成果显著,21种已被SCIE/SSCI收录的期刊代表了优势/前沿学科,或填补了学科空白,对世界一流期刊建设起到了推动作用。
