Developing Lexicons for Enhanced Sentiment Analysis in Software Engineering:An Innovative Multilingual Approach for Social Media Reviews

Sentiment analysis is becoming increasingly important in today’s digital age, with social media being a significantsource of user-generated content. The development of sentiment lexicons that can support languages other thanEnglish is a challenging task, especially for analyzing sentiment analysis in social media reviews. Most existingsentiment analysis systems focus on English, leaving a significant research gap in other languages due to limitedresources and tools. This research aims to address this gap by building a sentiment lexicon for local languages,which is then used with a machine learning algorithm for efficient sentiment analysis. In the first step, a lexiconis developed that includes five languages: Urdu, Roman Urdu, Pashto, Roman Pashto, and English. The sentimentscores from SentiWordNet are associated with each word in the lexicon to produce an effective sentiment score. Inthe second step, a naive Bayesian algorithm is applied to the developed lexicon for efficient sentiment analysis ofRoman Pashto. Both the sentiment lexicon and sentiment analysis steps were evaluated using information retrievalmetrics, with an accuracy score of 0.89 for the sentiment lexicon and 0.83 for the sentiment analysis. The resultsshowcase the potential for improving software engineering tasks related to user feedback analysis and productdevelopment.

Lexicon and Deep Learning-Based Approaches in Sentiment Analysis on Short Texts

Social media is an essential component of our personal and professional lives. We use it extensively to share various things, including our opinions on daily topics and feelings about different subjects. This sharing of posts provides insights into someone’s current emotions. In artificial intelligence (AI) and deep learning (DL), researchers emphasize opinion mining and analysis of sentiment, particularly on social media platforms such as Twitter (currently known as X), which has a global user base. This research work revolves explicitly around a comparison between two popular approaches: Lexicon-based and Deep learning-based Approaches. To conduct this study, this study has used a Twitter dataset called sentiment140, which contains over 1.5 million data points. The primary focus was the Long Short-Term Memory (LSTM) deep learning sequence model. In the beginning, we used particular techniques to preprocess the data. The dataset is divided into training and test data. We evaluated the performance of our model using the test data. Simultaneously, we have applied the lexicon-based approach to the same test data and recorded the outputs. Finally, we compared the two approaches by creating confusion matrices based on their respective outputs. This allows us to assess their precision, recall, and F1-Score, enabling us to determine which approach yields better accuracy. This research achieved 98% model accuracy for deep learning algorithms and 95% model accuracy for the lexicon-based approach.

LexDeep:Hybrid Lexicon and Deep Learning Sentiment Analysis Using Twitter for Unemployment-Related Discussions During COVID-19

The COVID-19 pandemic has spread globally,resulting in financialinstability in many countries and reductions in the per capita grossdomestic product.Sentiment analysis is a cost-effective method for acquiringsentiments based on household income loss,as expressed on social media.However,limited research has been conducted in this domain using theLexDeep approach.This study aimed to explore social trend analytics usingLexDeep,which is a hybrid sentiment analysis technique,on Twitter to capturethe risk of household income loss during the COVID-19 pandemic.First,tweet data were collected using Twint with relevant keywords before(9 March2019 to 17 March 2020)and during(18 March 2020 to 21 August 2021)thepandemic.Subsequently,the tweets were annotated using VADER(lexiconbased)and fed into deep learning classifiers,and experiments were conductedusing several embeddings,namely simple embedding,Global Vectors,andWord2Vec,to classify the sentiments expressed in the tweets.The performanceof each LexDeep model was evaluated and compared with that of a supportvector machine(SVM).Finally,the unemployment rates before and duringCOVID-19 were analysed to gain insights into the differences in unemploymentpercentages through social media input and analysis.The resultsdemonstrated that all LexDeep models with simple embedding outperformedthe SVM.This confirmed the superiority of the proposed LexDeep modelover a classical machine learning classifier in performing sentiment analysistasks for domain-specific sentiments.In terms of the risk of income loss,the unemployment issue is highly politicised on both the regional and globalscales;thus,if a country cannot combat this issue,the global economy will alsobe affected.Future research should develop a utility maximisation algorithmfor household welfare evaluation,given the percentage risk of income lossowing to COVID-19.

MELex: The Construction of Malay-English Sentiment Lexicon

Currently,the sentiment analysis research in the Malaysian context lacks in terms of the availability of the sentiment lexicon.Thus,this issue is addressed in this paper in order to enhance the accuracy of sentiment analysis.In this study,a new lexicon for sentiment analysis is constructed.A detailed review of existing approaches has been conducted,and a new bilingual sentiment lexicon known as MELex(Malay-English Lexicon)has been generated.Constructing MELex involves three activities:seed words selection,polarity assignment,and synonym expansions.Our approach differs from previous works in that MELex can analyze text for the two most widely used languages in Malaysia,Malay,and English,with the accuracy achieved,is 90%.It is evaluated based on the experimentation and case study approaches where the affordable housing projects in Malaysia are selected as case projects.This finding has given an implication on the ability of MELex to analyze public sentiments in the Malaysian context.The novel aspects of this paper are two-fold.Firstly,it introduces the new technique in assigning the polarity score,and second,it improves the performance over the classification of mixed language content.

Sexism in the English Lexicon

For a long time,there exists a considerable amount of sexism in English,especially in English lexicon.In this paper,the author will discuss some presentations of sexism in English lexicon,and try to analyze some factors which have a great influence on the existence of sexism in English.This paper wants to arouse more and more people to realize the importance and urgency of desexism.

A Comparative Analysis between English and Chinese Forensic Lexicon

Forensic linguistics, which is the interface between language and law, is a newly emerging interdiscipline in China. It belongs to neither the science of law nor the pure research category of linguistics, but it is an interdisciplinary subject based on these two disciplines. The linguistic issue in legal field is its key problem. At present, forensic linguistics in present China lays emphasis on written language instead of spoken language. This article gives a brief comparative analysis of Chinese and English forensic lexicon and the similarity of English and Chinese forensic lexicon. It also suggests that learners should view the differences between the two from the cultural perspective.

The Construction of Effective“Multidimensional Mental Lexicon of Second Language”in Second Language Vocabulary Teaching

The focus of the thesis is the construction of multidimensional mental lexicon of second language. It is made up of four dimensions—dimension of meaning, dimension of pronunciation, dimension of orthography and dimension of context so that through establishing these four dimensions, it comes into being.

Mental Lexicon Study and Its Enlightening to Incidental Vocabulary Acquisition of L2

The theories of mental lexicon explain how words are organized and accessed in human brain from the angle of psycho linguistics. It draws great interest to study on the field of psycholinguistics and SLA. This paper focuses on incidental vocabulary acquisition of L2 and explores how to assist learners to reinforce and expand their network of mental lexicon by applying all kinds of mental connection in order to promote the learners to acquire English vocabulary.

Lexicon PCM90数字混响器模拟自然混响声场的原理和应用

本文从室内声场的组成出发,以Lexicon PCM90这一优秀的数字混响器为例,较为详细地分析了录音节目制作中所必须且重要的周边设备——数字混响器模拟自然声场的工作原理以及其相应的应用问题。

The Importance of Auditory Discrimination in the Acquisition of Mental Lexicon and Reading Automation in Arabic-Speaking Students in Kenitra (Morocco)

Auditory discrimination is the ability to discriminate between words and sounds. Auditory discrimination can affect reading, spelling and writing. Several studies examined the correlation between auditory discrimination and reading performance. The aim of this study is to demonstrate the importance of auditory discrimination in the acquisition of mental lexicon and consequently the automation of reading in a sample of 101 students in their fourth year of primary education coming from four different schools in Kenitra (Morocco). The results analysis shows that reading scores correlated significantly with the auditory discrimination scores (r = 0.30, p 0.01). This proves that the inability to discriminate words causes a disability to store them in the mental lexicon, which makes it difficult to identify these words at a later encounter. This conclusion is supported by the significant correlation between reading and auditory and visual lexical decision tasks. In this study we were able to emphasize the importance of having good acoustic discrimination capacities for language development. Students who were successful at the auditory discrimination task are more successful at reading. A remediation program based on improving auditory discrimination capacities using the language assessment battery LABBEL could see reading performance improvement in these students.

Flexicon推出高性能聚氨酯水管

据英国媒体报道，全球领先的运输设备及系统的设计商和供应商Flexicon公司日前推出了一款聚氨酯涂层、镀锌钢材水管。

Sentiment Lexicon Construction Based on Improved Left-Right Entropy Algorithm

A novel method of constructing sentiment lexicon of new words(SLNW)is proposed to realize effective Weibo sentiment analysis by integrating existing lexicons of sentiments,lexicons of degree,negation and network.Based on left-right entropy and mutual information(MI)neologism discovery algorithms,this new algorithm divides N-gram to obtain strings dynamically instead of relying on fixed sliding window when using Trie as data structure.The sentiment-oriented point mutual information(SO-PMI)algorithm with Laplacian smoothing is used to distinguish sentiment tendency of new words found in the data set to form SLNW by putting new words to basic sentiment lexicon.Experiments show that the sentiment analysis based on SLNW performs better than others.Precision,recall and F-measure are improved in both topic and non-topic Weibo data sets.

The Emotional Lexicon and Its Correlates Following Traumatic Brain Injury

Traumatic brain injury (TBI) can often influence the way subjects process and cope with their emotional life. In spite of the huge amount of studies investigating facial emotion recognition in subjects with traumatic brain injury, none of them has examined if their emotional lexicon, i.e. the ability to express emotions through words, may be affected. In this case-control study, we investigated the emotional lexicon of a group of 16 severe TBI subjects, comparing their performances with an healthy control group. A set of 25 visual stimuli (10 single picture images, 5 cartoon story pictures and 10 video clips) were selected. All the stimuli were chosen for their high emotional content by ten blind judges. The participants were asked to describe the stimuli, focusing on their emotional content. To get a better understanding of the correlates of emotional lexicon, all the participants were administered with the backward version of the Digit Span test, the Ekman and Friesen 60 Faces, the 20-Item Toronto Alexithymia Scale and the Empathy Quotient. Results pointed out a significant difference between TBI subjects and healthy controls only for cartoon story and video clip description. Conversely, TBI subjects performed similarly to controls when asked to describe the single picture images. A significant correlation was found in TBI subjects between the results of the Digit Span and number of emotional words, while no correlation was detected between emotional terms and the three scales used to assess TBI subjects’ emotional profile. These outcomes highlight that, for more complex stimuli, difficulties in emotional lexicon may depend on factors other than empathy, alexythimia or emotion recognition. These difficulties seem to be related to reduced working memory capacity, which prevent the subjects from correctly processing the emotional content of stimuli.

简析Lexicon MX400立体声效果器的使用方法

Lexicon MX400（下面简称MX400）于2006年6月正式进入我国,现在已经有10个年头了,但是现在此款效果器的使用方法,国内舞美灯光师还不能很好掌握,本文简要介绍一下Lexicon MX400立体声效果器的使用方法和操作心得。MX400型效果器是一款立体声效果器,他内部集合了4台处理器,并且可以单声道叠加输出你所需要的效果。

On the Cognition of Second Language Mental Lexicon and Teaching Chinese as a Foreign Language

Teaching Chinese as a foreign language is actually the teaching of Chinese as a second language by international Chinese teachers.People must learn vocabulary as a language element in the process of language acquisition.Without vocabulary,there is no language.When we master the vocabulary of a language,we rely on mental lexicon,which is vocabulary that has been stored in the brain for a long time.Through the study of second language mental lexicon,it can be used effectively,and corresponding teaching methods can be used in the vocabulary teaching of Chinese as a foreign language to help students learn Chinese quickly and effectively.

Language Features of Politeness at Lexicon Level in English, Japanese and Chinese

Courtesy language, as an indispensable part of communication, occurs in all languages. However, due to the cultural diversity, different languages have different laws and regulations in the choice of courtesy language, which is very important in cross culture communication. It is significant and instructive to study the similarities and differences of the courtesy language. The article aims to study the language features of politeness at lexicon, syntactic and pragmatic level in English, Japanese and Chinese as well as the underlying reasons and culture roots of the diversities, to make cross-culture communication better.

Analysis on Sexism in English Lexicons from the Perspective of Metaphor

Metaphors We Live By lieve that metaphor is not only the form of human language, but the fundamental mode of human thought and behavior. This thesiswill make further analyses of the vocabularies reflecting sexism from three aspects:animal metaphor, plant metaphor and food meta-phor. In addition, this paper makes a simple analysis of the causes of the phenomenon. Thereby people can have a better under-standing of the language system and the appropriate usage of language.

The Comparative Study of Two Translated Texts on Huangdirent Translating Styles o'n s Internal Classics——Simple Analysis on the Diffe Culture-Specific Lexicon, Figure of Speech and Four-Chinese-Character Structures

Huangdi's Internal Classics(Neijin) is one of the most important ancient medical classics, which plays far-reaching influence in medical field. More and more domestic and overseas scholars published their translated texts on Neijing. Due to the diversity of editions and different understanding, the translating styles and contents are widely different. This study will focus on the different translating styles on culture-specific lexicon、figure of speech and four-Chinese-character structures in Neijin.

BMS从Lexicon得到13种神经病学化合物

Bristol-Myers Squibb公司与Lexicon Genetics公司签订范围广泛的协议，从而得到Lexicon公司在神经科学领域中的14个药物发现项目中的13个，加上Genome5000项目中将来发现的专营权利。此外。

王者现身——评Lexicon RT-10通吃型播放机

尽管DVD-Audio和SACD的音质有了巨大的、无可置疑的改进，但人们对它们的接受速度却逐渐地减慢下来了。表面上这首先要归罪于两种高格式之间残酷的争夺战，而让事情变得更加糟糕的则是唱片公司始终没有就一种不加版权限制的数字连接方式达成一种标准。