The dominant of Bloggers in Malaysian politics through social networks

Every country in this world has own political issues. In Malaysia for example, political issues played an important role that can influence other factors such as social and economy. As we all know, political factor can give positive and negative effect to a situation in Malaysia. The frequent usage of computer nowadays by Malaysian people helps in spreading information and news about political situation in Malaysia through cyberspace. In this paper, we use web mining system with Artificial Immune System (AIS) to regain a small group of relevant websites and webpages on political issues in Malaysia. To analyze the relationship between website and webpages, the concept of social networks will be used. Result from the web mining system with AIS will be used to understand the impact of social network to the political situation in Malaysia

The big five: Discovering linguistic characteristics that typify distinct personality traits across Yahoo! answers members

Indexación: Scopus.This work was partially supported by the project FONDECYT “Bridging the Gap between Askers and Answers in Community Question Answering Services” (11130094) funded by the Chilean Government.In psychology, it is widely believed that there are five big factors that determine the different personality traits: Extraversion, Agreeableness, Conscientiousness and Neuroticism as well as Openness. In the last years, researchers have started to examine how these factors are manifested across several social networks like Facebook and Twitter. However, to the best of our knowledge, other kinds of social networks such as social/informational question-answering communities (e.g., Yahoo! Answers) have been left unexplored. Therefore, this work explores several predictive models to automatically recognize these factors across Yahoo! Answers members. As a means of devising powerful generalizations, these models were combined with assorted linguistic features. Since we do not have access to ask community members to volunteer for taking the personality test, we built a study corpus by conducting a discourse analysis based on deconstructing the test into 112 adjectives. Our results reveal that it is plausible to lessen the dependency upon answered tests and that effective models across distinct factors are sharply different. Also, sentiment analysis and dependency parsing proven to be fundamental to deal with extraversion, agreeableness and conscientiousness. Furthermore, medium and low levels of neuroticism were found to be related to initial stages of depression and anxiety disorders. © 2018 Lithuanian Institute of Philosophy and Sociology. All rights reserved.https://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/view/275

LCSTS: A Large Scale Chinese Short Text Summarization Dataset

Automatic text summarization is widely regarded as the highly difficult problem, partially because of the lack of large text summarization data set. Due to the great challenge of constructing the large scale summaries for full text, in this paper, we introduce a large corpus of Chinese short text summarization dataset constructed from the Chinese microblogging website Sina Weibo, which is released to the public {http://icrc.hitsz.edu.cn/Article/show/139.html}. This corpus consists of over 2 million real Chinese short texts with short summaries given by the author of each text. We also manually tagged the relevance of 10,666 short summaries with their corresponding short texts. Based on the corpus, we introduce recurrent neural network for the summary generation and achieve promising results, which not only shows the usefulness of the proposed corpus for short text summarization research, but also provides a baseline for further research on this topic.Comment: Recently, we received feedbacks from Yuya Taguchi from NAIST in Japan and Qian Chen from USTC of China, that the results in the EMNLP2015 version seem to be underrated. So we carefully checked our results and find out that we made a mistake while using the standard ROUGE. Then we re-evaluate all methods in the paper and get corrected results listed in Table 2 of this versio

Satirical News Detection and Analysis using Attention Mechanism and Linguistic Features

Satirical news is considered to be entertainment, but it is potentially deceptive and harmful. Despite the embedded genre in the article, not everyone can recognize the satirical cues and therefore believe the news as true news. We observe that satirical cues are often reflected in certain paragraphs rather than the whole document. Existing works only consider document-level features to detect the satire, which could be limited. We consider paragraph-level linguistic features to unveil the satire by incorporating neural network and attention mechanism. We investigate the difference between paragraph-level features and document-level features, and analyze them on a large satirical news dataset. The evaluation shows that the proposed model detects satirical news effectively and reveals what features are important at which level.Comment: EMNLP 2017, 11 page

Preface

Thiis is the preface introducing the volum

Empirical Analysis of Agricultural Productivity: Growth in Benin and Mainly Factors which Influence Growth

This study examined changes in agricultural productivity at Benin in the context of diverse institutional arrangements using Data Envelopment Analysis (DEA).A time series data which consists of information on agricultural production and means of production were obtained from World Research Institute database, INSAE and rainfall data from AMMA database. The information was for a 43-year period (1961-2003); DEA method was used to measure Malquist index of total factor productivity to evaluate technical change efficiency and technological efficiency change across the country’s 12 provinces. A decomposition of TFP measures revealed whether the performance of factors productivity is due to technological change or technical efficiency change over the reference period. The study further examined the effect of land quality, agriculture labor, and selected governance indicators such as government effectiveness and openness on productivity growth. All the variables included in the model are significant effect on the TPF and the country agriculture growth. They equally performed well in terms of expected relationship with TFP except land quality index which unexpectedly had an inverse relationship with TFP.Data Envelopment Analysis, Efficiency, Productivity, Benin, Agribusiness, N57, C01, C23,

The Tyranny of Transparency: Auto-immunity in The Teaching Machine

This article proposes that the prime ideals of the university - those of truth, knowledge, justice, and emancipation - are also those that currently produce unjust practices "outside" and "within". Using the work of Jacques Derrida and Paul Virilio, the article argues that the central problem of the university today consists not so much of a neo-liberalisation, but of the speeding-up of these ideals through their enmeshment with techniques of calculation, vision, and prediction. The current university therefore suffers from what it with Derrida identifies as an "auto-immune disease," in which the acceleration of its foundational aspirations have led to a near-total subjugation of all and everything to an oppressive quest for transparency. However, the article proposes via Virilio that this totalising transparency paradoxically also produces more blindness, accidents, and unknowability. It hopes to illustrate this with some examples in the teaching scene as well by working through some of its own conceptual tensions. The other logic of the university today, the article finally proposes, consists of a "dark" or stealth functionality, opening up the promise of a radically different future and unanticipated resistance despite itself