Measuring the Influence and Intensity of Customer’s Sentiments in Facebook and Twitter

Organisations these days are actively using social media platforms to engage with potential and existing customers and monitor what they say about the organisation’s product or service. The most important area within social media monitoring lies in how to gain insight for sentiment analysis. Sentiment analysis helps in effective evaluation of customer’s sentiments in real time and takes on a special meaning in the context of online social networks like Twitter and Facebook, which collectively represent the largest online forum available for public opinion. Sentiment Analysis is not about retrieving and analyzing the analytics purely on the basis of positive, negative or neutral sentiment. It is imperative to assess the influencers of the sentiments in terms of Retweet and Share option used by them on Twitter and Facebook platform respectively. Measuring the intensity is other important aspect of sentiment analysis process. What kind of nouns, adjectives, verbs and adverbs are used in the opinion across the Twitter and Facebook platform matters as well since it exhibits the intensity of the underlying emotion in the text written. This study was conducted to propose a framework to identify and analyse the positive and negative sentiments present in Twitter and Facebook platforms and an algorithm was prepared to measure the intensity and influence of the positive, negative sentiment in particular using the document and sentence level analysis technique

A Comparative Analysis of Opinion Mining and Sentiment Classification in Non-english Languages

In the past decade many opinion mining and sentiment classification studies have been carried out for opinions in English. However, the amount of work done for non-English text opinions is very limited.In this review, we investigate opinion mining and sentiment classification studies in three non-English languages to find the classification methods and the efficiency of each algorithm used in these methods. It is found that most of the research conducted for non-English has followed the methods used in the English language with onlylimited usage of language specific properties, such as morphological variations. The application domains seem to be restricted to particular fields and significantly less research has been conducted in cross domains. Keywords—Natural Language processing, Text mining, Machine Learning

Public Opinion Analysis Using Hadoop

Recent technological advances in devices, computing, and social networking have revolutionized the world but have also increased the amount of data produced by humans on a large scale. If you collect this data in the form of disks, it may fill an entire football field. According to studies, 2.5 billion gigabytes of new data is generated every day and 2.5 petabytes of data is collected every hour. This rate is still growing enormously. Though all this information produced is meaningful and can be useful when processed, it gets neglected. Social media has gained massive popularity nowadays. Twitter makes it easy to engage users in expressing, sharing and discussing hot latest topics but these public expressions and views are hard to analyze due to the bigger size of the data created by Twitter. In order to perform analysis and predictions over the hot topics in society, latest technologies are needed. The most popular solution for this is Hadoop. Hadoop acts as an open-source framework for developing and executing distributed applications that process very large amounts of data. It stores and process big data in a distributed fashion on large clusters of commodity hardware. The risk, of course, in running on commodity machines is how to handle failure. Hadoop is built with the assumption that hardware will fail and as such, it can easily handle most failures. Hadoop can be used for developing and executing distributed applications that process very large amounts of data. It provides a suitable environment needed for treating or processing huge data. Our job is to extract and store data into its file system and query the data according to the desired output. We propose to perform analysis on Public opinion expressed over Twitter regarding the trending topics of the society by using Apache Hadoop framework along with its services Apache Flume and Apache Hive

Natural Language Processing: Emerging Neural Approaches and Applications

This Special Issue highlights the most recent research being carried out in the NLP field to discuss relative open issues, with a particular focus on both emerging approaches for language learning, understanding, production, and grounding interactively or autonomously from data in cognitive and neural systems, as well as on their potential or real applications in different domains

Leveraging writing systems changes for deep learning based Chinese affective analysis

Affective analysis of social media text is in great demand. Online text written in Chinese communities often contains mixed scripts including major text written in Chinese, an ideograph-based writing system, and minor text using Latin letters, an alphabet-based writing system. This phenomenon is referred to as writing systems changes (WSCs). Past studies have shown that WSCs often reflect unfiltered immediate affections. However, the use of WSCs poses more challenges in Natural Language Processing tasks because WSCs can break the syntax of the major text. In this work, we present our work to use WSCs as an effective feature in a hybrid deep learning model with attention network. The WSCs scripts are first identified by their encoding range. Then, the document representation of the text is learned through a Long Short-Term Memory model and the minor text is learned by a separate Convolution Neural Network model. To further highlight the WSCs components, an attention mechanism is adopted to re-weight the feature vector before the classification layer. Experiments show that the proposed hybrid deep learning method which better incorporates WSCs features can further improve performance compared to the state-of-the-art classification models. The experimental result indicates that WSCs can serve as effective information in affective analysis of the social media text

Film policy and the emergence of the cross-cultural: exploring crossover cinema in Flanders (Belgium)

With several films taking on a cross-cultural character, a certain ‘crossover trend’ may be observed within the recent upswing of Flemish cinema (a subdivision of Belgian cinema). This trend is characterized by two major strands: first, migrant and diasporic filmmakers finally seem to be emerging, and second, several filmmakers tend to cross the globe to make their films, hereby minimizing links with Flemish indigenous culture. While paying special attention to the crucial role of film policy in this context, this contribution further investigates the crossover trend by focusing on Turquaze (2010, Kadir Balci) and Altiplano (2009, Peter Brosens & Jessica Woodworth)

From Electocracy to Democracy: Coalition, Cohesion, and Function

Generally, democracy composes the elements of election, rights and liberty, middle class, and the rules of law to govern the state and people. Malaysia had limited experience of a democracy that was absent from the elements above. It had its first election during the colonial era that dictates the function of an election.  Later, the election becomes routine every five years that makes it an electocracy or a political culture lacks political literacy. The post-independence context of a strong leader and a dominant party alliance to rule the state and society resulted in making political analysts criticizing Malaysia as a state of the quasi, semi, and syncretic democracy. The recent power transition with no record of violence in Fourteen General Election (2018) proves that the previous label of democracy in Malaysia is obsolete. Therefore, the analysis tool of assessing Malaysian politics is still dormant with the Western perspective of the two-party system, the end of racial politics hence assuming the beginning of an ideology-based party and the belief that the new Malaysia will fit in the western mold of democracy. The robust information technology via social media harvesting new challenges for democracy in Malaysia. It cannot escape the spread of fake news or disinformation to influence voters. The game of fake news has put Malaysia as a state of electocracy full of unskilled politicians to govern the multiethnic nation