A novel approach for efficient stance detection in online social networks with metaheuristic optimization

In the 19th and 20th centuries, social networks have been an important topic in a wide range of fields from sociology to education. However, with the advances in computer technology in the 21st century, significant changes have been observed in social networks, and conventional networks have evolved into online social networks. The size of these networks, along with the large amount of data they generate, has introduced new social networking problems and solutions. Social network analysis methods are used to understand social network data. Today, several methods are implemented to solve various social network analysis problems, albeit with limited success in certain problems. Thus, the researchers develop new methods or recommend solutions to improve the performance of the existing methods. In the present paper, a novel optimization method that aimed to classify social network analysis problems was proposed. The problem of stance detection, an online social network analysis problem, was first tackled as an optimization problem. Furthermore, a new hybrid metaheuristic optimization algorithm was proposed for the first time in the current study, and the algorithm was compared with various methods. The analysis of the findings obtained with accuracy, precision, recall, and F-measure classification metrics demonstrated that our method performed better than other methods.     

一种基于迁移学习及多表征的微博立场分析方法

立场分析旨在发现用户对特定目标对象所持的观点态度。针对现有方法往往难以克服标注数据匮乏及微博文本中大量未登录词等导致的分词误差的问题,提出了基于迁移学习及字、词特征混合的立场分析方法。首先,将字、词特征输入深度神经网络,级联两者隐藏层输出,复现由分词错误引起的缺失语义信息;然后,利用与立场相关话题的辅助数据训练话题分类模型(父模型),得到更为有效的句子特征表示;接着,以父模型参数初始化立场分析模型(子模型),从辅助数据(话题分类数据)迁移知识能加强句子的语义表示能力;最后,使用有标注数据微调子模型参数并训练分类器。在NLPCC-2016任务4的语料上进行实验,F1值达72.2%,优于参赛团队的最佳成绩。实验结果表明,该方法可提高立场分类性能,同时缓解分词误差带来的影响。     

热水与光伏系统集光器的姿态区别

热能和电能是建筑必需的能量形式,因此在太阳能建筑中热水和光伏系统应同时考虑。为了扩大太阳能在建筑能源结构,特别是多层和高层建筑能源结构中的比例,集光器的安装部位也不应局限于屋顶,而必须向立面拓展。不同形式的能量其主要使用的季节也不同,因此集光器的姿态和部位应有明显区别。该文拟从辐射条件、供需同步性及对遮挡及组合面变化的敏感性方面对影响集光器姿态的因素进行分析,并结合设计实例进行探讨。     

A novel approach to stance detection in social media tweets by fusing ranked lists and sentiments

Stance detection is a relatively new concept in data mining that aims to assign a stance label (favor, against, or none) to a social media post towards a specific pre-determined target. These targets may not be referred to in the post, and may not be the target of opinion in the post. In this paper, we propose a novel enhanced method for identifying the writer’s stance of a given tweet. This comprises a three-phase process for stance detection: (a) tweets preprocessing; here we clean and normalize tweets (e.g., remove stop-words) to generate words and stems lists, (b) features generation; in this step, we create and fuse two dictionaries for generating features vector, and lastly (c) classification; all the instances of the features are classified based on the list of targets. Our innovative feature selection proposes fusion of two ranked lists (top-$k$) of term frequency-inverse document frequency (tf-idf) scores and the sentiment information. We evaluate our method using six different classifiers: $K$ nearest neighbor (K-NN), discernibility-based K-NN, weighted K-NN, class-based K-NN, exemplar-based K-NN, and Support Vector Machines. Furthermore, we investigate the use of Principal Component Analysis and study its effect on performance. The model is evaluated on the benchmark dataset (SemEval-2016 task 6), and the results significance is determined using t-test. We achieve our best performance of macro $F$-score (averaged across all topics) of 76.45% using the weighted K-NN classifier. This tops the current state-of-the-art score of 74.44% on the same dataset.     

遗传神经网络在车身姿态测量中的应用

本文提出了一种精简的车身姿态测量方案,利用单个三维加速度计,通过遗传神经网络映射输出车身姿态角。该方案对加速度映射姿态角进行了详尽立体的分析,利用神经网络的非线性映射能力、泛化能力和容错能力对系统误差进行补偿后输出。实测数据仿真实验结果显示,该方案满足精度要求,确实可行。     

HeadlineStanceChecker: Exploiting summarization to detect headline disinformation

The headline of a news article is designed to succinctly summarize its content, providing the reader with a clear understanding of the news item. Unfortunately, in the post-truth era, headlines are more focused on attracting the reader’s attention for ideological or commercial reasons, thus leading to mis- or disinformation through false or distorted headlines. One way of combating this, although a challenging task, is by determining the relation between the headline and the body text to establish the stance. Hence, to contribute to the detection of mis- and disinformation, this paper proposes an approach (HeadlineStanceChecker) that determines the stance of a headline with respect to the body text to which it is associated. The novelty rests on the use of a two-stage classification architecture that uses summarization techniques to shape the input for both classifiers instead of directly passing the full news body text, thereby reducing the amount of information to be processed while keeping important information. Specifically, summarization is done through Positional Language Models leveraging on semantic resources to identify salient information in the body text that is then compared to its corresponding headline. The results obtained show that our approach achieves 94.31% accuracy for the overall classification and the best FNC-1 relative score compared with the state of the art. It is especially remarkable that the system, which uses only the relevant information provided by the automatic summaries instead of the whole text, is able to classify the different stance categories with very competitive results, especially in the discuss stance between the headline and the news body text. It can be concluded that using automatic extractive summaries as input of our approach together with the two-stage architecture is an appropriate solution to the problem.     

The influence of boot stiffness on gait kinematics and kinetics during stance phase

In the study, the influence of different boot prototype stiffness on gait kinematics and kinetics was investigated. The boot stiffness was determined by force-deformation measurement while pressing the foot model inserted into the boot by a custom-made robot. Gait analysis was carried out in nine neurologically intact subjects during walking while wearing two different boots with and without carrying a backpack, and differences were statistically tested using ANOVA.

The results indicated distinctions in the boot shaft and vamp stiffness. The boot with a softer boot shaft enabled a wider range of motion in the ankle joint leading to more power generation in the ankle joint during the push-off, increased step length and gait velocity. The backpack mostly influenced the pelvis and trunk kinematics.

The study has demonstrated the influence of boot shaft stiffness on biomechanical gait parameters and its importance for push-off that manufacturers should take into consideration when optimizing the footwear performance.     

The Method of Levels of Abstraction

The use of “levels of abstraction” in philosophical analysis (levelism) has recently come under attack. In this paper, I argue that a refined version of epistemological levelism should be retained as a fundamental method, called the method of levels of abstraction. After a brief introduction, in section “Some Definitions and Preliminary Examples” the nature and applicability of the epistemological method of levels of abstraction is clarified. In section “A Classic Application of the Method of Abstraction”, the philosophical fruitfulness of the new method is shown by using Kant’s classic discussion of the “antinomies of pure reason” as an example. In section “The Philosophy of the Method of Abstraction”, the method is further specified and supported by distinguishing it from three other forms of “levelism”: (i) levels of organisation; (ii) levels of explanation and (iii) conceptual schemes. In that context, the problems of relativism and antirealism are also briefly addressed. The conclusion discusses some of the work that lies ahead, two potential limitations of the method and some results that have already been obtained by applying the method to some long-standing philosophical problems.