Epilogue

In general, historians have put too much trust in the negative opinion of Jovian’s person and reign held by Ammianus Marcellinus, Libanius, and other (pagan) writers who display an obvious nostalgia for Julian and his rule. Although Jovian died before his skills as ruler could be truly tested, it is fair to say that his eight-months rule was not only eventful, but also a promising new start for the Roman Empire after the turbulent and confusing reign of Julian. The presentation of Jovian as a new Constantine in the Jovian Narrative served the interests of Edessa in its christological conflict with Antioch and Constantinople under Justinian and is linked to a portrayal of Edessa as a pristine and ancient Christian city. In addition, the story expresses the wish for peaceful coexistence in northern Mesopotamia between Rome and Persia, as was accomplished by Jovian’s treaty with Shapur.

The North Shore’s Forgotten Horse Tramway: The Devonport and Lake Takapuna Tramway Company

One of New Zealand’s last horse tramways, the Devonport and Lake Takapuna Tramway Company has been largely neglected by historians, and those who have reported on it often include or imply incorrect information. This has resulted in a universally negative opinion of the tramway that briefly shuttled passengers between Victoria Wharf and Cheltenham Beach in Devonport, Auckland, between 1886 and 1888. This article examines the company’s history from the perspectives of those who witnessed its rise and fall, and includes technical details from primary sources, observations by reporters, and additional information derived from photographs, maps, and government documents.

Analyzing sentiment system to specify polarity by lexicon-based

Currently, sentiment analysis into positive or negative getting more attention from the researchers. With the rapid development of the internet and social media have made people express their views and opinion publicly. Analyzing the sentiment in people views and opinion impact many fields such as services and productions that companies offer. Movie reviewer needs many processing to be prepared to detect emotion, classify them and achieve high accuracy. The difficulties arise due of the structure and grammar of the language and manage the dictionary. We present a system that assigns scores indicating positive or negative opinion to each distinct entity in the text corpus. Propose an innovative formula to compute the polarity score for each word occurring in the text and find it in positive dictionary or negative dictionary we have to remove it from text. After classification, the words are stored in a list that will be used to calculate the accuracy. The results reveal that the system achieved the best results in accuracy of 76.585%.

DISINFORMASI PEMBAKARAN BENDERA KALIMAT TAUHID

There was a burning of tauhid flag on 28 oct 2018 at kec limabngan garut. It was known as the flag of hti. This action became widely spread out through the video with many argumentation and opinion. Besides, there was false infirmation about flag burning. This study focused to give description text analysis, practical discourse analysis and socio cultural on this burning flag incident. The object of the study is the false information of tauhid flag burning. Data collection technique is documentation from turnbackhiax.id. Data analysis uses critical discourse analysis by fairclough. From the analysis, it can be concluded that there is a negative opinion construction toward muslim. Second, this negative framing has also a political situation at that time.

Suspicious Activity Detection of Twitter and Facebook using Sentimental Analysis

The purpose of this study is to evaluate the criminal behavior on the social media platforms and to classify the gathered data effectively as negative, positive, or neutral in order to identify a suspect. In this study, data was collected from two platforms, Twitter and Facebook, resulting in the creation of two datasets. The following findings have been pointed out from this study: Initially, VADER twitter sentimental analysis showed that out of 5000 tweets 50.8% people shared a neutral opinion, 39.2% shared negative opinion and only 9.9% showed positive opinion. Secondly, on Facebook, the majority of people showed a neutral response which is 55.6%, 38.9% shared positive response and only 5.6% shared negative opinion. Thirdly, the score of sentiments and engagement in every post affects the intensities of sentiments.

Hysteria-epilepsy and castration.

Based on his observations, the author expresses a negative opinion about the significance of castration in hysteria-epilepsy. Produced his castration was undertaken not for the sake of nervous suffering, as a result of complaints of patients on pain in the abdomen, caused by pathological processes of the uterine appendages in both Estero-epileptic seizures.

Aspects of Motivation and Engagement of Employees in Their Work Based on the Example of Mining Companies

The paper presents an analysis of selected aspects of motivation and engagement of hard coal mine employees working in longwall faces. The analysis of survey results covers selected questions from a broader survey conducted in the analyzed mining companies. The miners had a negative opinion on the incentive programme in their workplaces, stating that it is ineffective. The survey also included factors affecting the engagement of the entire research sample in their work, showing their significance level for the respondents.

Sarcasm Detection Using Multi-Channel Attention Based BLSTM On News Headline

Sarcasm is often used to express a negative opinion using positive or intensified positive words in social media. This intentional ambiguity makes sarcasm detection, an important task of sentiment analysis. Detecting a sarcastic tone in natural language hinders the performance of sentiment analysis tasks. The majority of the studies on automatic sarcasm detection emphasize on the use of lexical, syntactic, or pragmatic features that are often unequivocally expressed through figurative literary devices such as words, emoticons, and exclamation marks. In this paper, we introduce a multi-channel attention-based bidirectional long-short memory (MCAB-BLSTM) network to detect sarcastic headline on the news. Multi-channel attention-based bidirectional long-short memory (MCAB-BLSTM) proposed model was evaluated on the news headline dataset, and the results-compared to the CNN-LSTM and Hybrid Neural Network were excellent.