Search results for: contrastive topic

Authors: R. A. S. Zacarias

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Interlingual is one of the most complex, and engaging one among the several perspectives in lexicography. This is because it involves contacts and contrasts between two or more languages. Considering the fact that translation equivalence goes beyond a mere fixed relation of correspondence, understanding the differences and similarities between linguistic categories by pairs of languages is the basis for effective translations. One of the theoretical approaches that have proved useful in finding improved solutions for enhance translation equivalents for bilingual dictionaries is contrastive linguistics. This paper presents an applied qualitative research based on exploratory and descriptive approaches. This is achieved through an error analysis of students’ errors as well as by a contrastive analysis of Portuguese and English verb systems.

Keywords: bilingual lexicography, contrastive linguistics, translation equivalent, Portuguese-English

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Authors: Hayat Omar

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Languages provide speakers with a wide range of linguistic units to organize and deliver information. There are several ways to verbally express the mental representations of events. According to the linguistic tools they have acquired, speakers select the one that brings out the most communicative effect to convey their message. Our study focuses on two markers, -mm and dämmo, in Amharic (Ethiopian Semitic language). Our aim is to examine, from a developmental perspective, how they are used by speakers. We seek to distinguish the communicative and pragmatic functions indicated by means of these markers. To do so, we created a corpus of sixty narrative productions of children from 5-6, 7-8 to 10-12 years old and adult Amharic speakers. The experimental material we used to collect our data is a series of pictures without text 'Frog, Where are you?'. Although -mm and dämmo are each used in specific contexts, they are sometimes analyzed as being interchangeable. The suffix -mm is complex and multifunctional. It marks the end of the negative verbal structure, it is found in the relative structure of the imperfect, it creates new words such as adverbials or pronouns, it also serves to coordinate words, sentences and to mark the link between macro-propositions within a larger textual unit. -mm was analyzed as marker of insistence, topic shift marker, element of concatenation, contrastive focus marker, 'bisyndetic' coordinator. On the other hand, dämmo has limited function and did not attract the attention of many authors. The only approach we could find analyzes it in terms of 'monosyndetic' coordinator. The paralleling of these two elements made it possible to understand their distinctive functions and refine their description. When it comes to marking a referent, the choice of -mm or dämmo is not neutral, depending on whether the tagged argument is newly introduced, maintained, promoted or reintroduced. The presence of these morphemes explains the inter-phrastic link. The information is seized by anaphora or presupposition: -mm goes upstream while dämmo arrows downstream, the latter requires new information. The speaker uses -mm or dämmo according to what he assumes to be known to his interlocutors. The results show that -mm and dämmo, although all the speakers use them both, do not always have the same scope according to the speaker and vary according to the age. dämmo is mainly used to mark a contrastive topic to signal the concomitance of events. It is more commonly used in young children’s narratives (F(3,56) = 3,82, p < .01). Some values of -mm (additive) are acquired very early while others are rather late and increase with age (F(3,56) = 3,2, p < .03). The difficulty is due not only because of its synthetic structure but primarily because it is multi-purpose and requires a memory work. It highlights the constituent on which it operates to clarify how the message should be interpreted.

Keywords: acquisition, cohesion, connection, contrastive topic, contrastive focus, discourse marker, pragmatics

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Authors: Lijuan Zhou, Mengqi Wu, Changyong Niu

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Attributed graph clustering can utilize the graph topology and node attributes to uncover hidden community structures and patterns in complex networks, aiding in the understanding and analysis of complex systems. Utilizing contrastive learning for attributed graph clustering can effectively exploit meaningful implicit relationships between data. However, existing attributed graph clustering methods based on contrastive learning suffer from the following drawbacks: 1) Complex data augmentation increases computational cost, and inappropriate data augmentation may lead to semantic drift. 2) The selection of positive and negative samples neglects the intrinsic cluster structure learned from graph topology and node attributes. Therefore, this paper proposes a method called self-supervised Attributed Graph Clustering with Dual Contrastive Loss constraints (AGC-DCL). Firstly, Siamese Multilayer Perceptron (MLP) encoders are employed to generate two views separately to avoid complex data augmentation. Secondly, the neighborhood contrastive loss is introduced to constrain node representation using local topological structure while effectively embedding attribute information through attribute reconstruction. Additionally, clustering-oriented contrastive loss is applied to fully utilize clustering information in global semantics for discriminative node representations, regarding the cluster centers from two views as negative samples to fully leverage effective clustering information from different views. Comparative clustering results with existing attributed graph clustering algorithms on six datasets demonstrate the superiority of the proposed method.

Keywords: attributed graph clustering, contrastive learning, clustering-oriented, self-supervised learning

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Authors: Maria Istvanova

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The acquisition of the correct pronunciation in Chinese is closely linked to the initial phase of the study. Based on the contrastive analysis, we determine the differences in the pronunciation of stop consonants in Chinese and Slovak taking into consideration the place and manner of articulation to gain a better understanding of the students' main difficulties in the process of acquiring correct pronunciation of Chinese stop consonants. We employ the software Praat for the analysis of the recorded samples with an emphasis on the pronunciation of the students with a varying command of Chinese. The comparison of the VOT length for the individual consonants in the students' pronunciation and the pronunciation of the native speaker exposes the differences between the correct pronunciation and the deviant pronunciation of the students.

Keywords: Chinese, contrastive analysis, Praat, pronunciation, Slovak.

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Authors: Abubakar Maikudi

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Contrastive analysis is the method of analyzing the structure of any two languages with a view to determining the possible differential aspects of their systems irrespective of their genetic affinity or level of development. Contrastive analysis of two languages becomes useful when it is adequately describing the sound structure and grammatical structure of two languages, with comparative statements giving emphasis to the compatible items in the two systems. This research work uses comparative analysis theory to analyze adjective and adjectival phrases in Hausa and Yorùbá languages. The Hausa language belongs to the Chadic family of the Afro-Asiatic phylum, while the Yorùbá language belongs to the Benue-Congo family of the Niger-Congo phylum. The findings of the research clearly demonstrated that there are significant similarities in the adjectival phrase constructions of the two languages, i.e., nominal (Head) and post-nominal (Post-Head) use of the adjective, predicative function of an adjective, use of the reduplicative adjective, use of the comparative and superlative adjective, etc. However, there are dissimilarities in the adjectival phrase of the two languages in gender/number agreement and pre-nominal (Post-Head) use of adjectives.

Keywords: genetic affinity, contrastive analysis, phylum, pre-head, post-head

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Authors: Mostafa ‘Neo’ Mohsenvand, Mohammad Rasool Izadi, Pattie Maes

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EEG-based biometrics (user identification) has been explored on small datasets of no more than 157 subjects. Here we show that the accuracy of modern supervised methods falls rapidly as the number of users increases to a few thousand. Moreover, supervised methods require a large amount of labeled data for training which limits their applications in real-world scenarios where acquiring data for training should not take more than a few minutes. We show that using contrastive learning for pre-training, it is possible to maintain high accuracy on a dataset of 2130 subjects while only using a fraction of labels. We compare 5 different self-supervised tasks for pre-training of the encoder where our proposed method achieves the accuracy of 96.4%, improving the baseline supervised models by 22.75% and the competing self-supervised model by 3.93%. We also study the effects of the length of the signal and the number of channels on the accuracy of the user-identification models. Our results reveal that signals from temporal and frontal channels contain more identifying features compared to other channels.

Keywords: brainprint, contrastive learning, electroencephalo-gram, self-supervised learning, user identification

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Authors: Tosin Samson Olagunju

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This study is a contrastive study of affixation in Ipe and Yoruba Languages with the aim of looking at the implications for English pedagogy. This study, with the use of Hocket's Theory of Item and Arrangement and Word and Paradigm (as expatiated by Crystal), examines the aspect of affixation in Ipe and Yoruba Languages with the help of contrastive analysis which provides a basis for contrasting the morphological patterns of two different indigenous languages. It examines four affixes: prefix, infix, interfix, and suffix with numerous examples in the languages under investigation. The study is corpus based as it depends primarily on the words available in the lexicon of the languages under examination. Data were elicited from both monolingual and bilingual native-speakers of Ipe Language and Yoruba Language in Ipe-Akoko and Oyo respectively. Ibadan 400-wordlist was utilised as a tool for collecting data from informants who are between age fifty and seventy through audio recording as it is believed that they are the custodians of culture and tradition. Consequently, the study reveals that Ipe and Yoruba morphology have affixation such as prefix, interfix, and suffix. It also finds out that 'infix' is an unproductive aspect in English, Ipe, and Yoruba; although a few examples are in English. Interfix is very productive in Ipe and Yoruba but not in English at all. Phonologically, it is discovered that Ipe language has the two dental fricative consonants just like the English language, i.e., /Ɵ/ and /ð/. This is rare among the indigenous languages in Nigeria. This research believes that in the teaching of English consonants to the people of Ipe-Akoko, such areas will be taught with ease. The study concludes that morphological processes of Nigerian indigenous languages are studied the more so that they will not face endangerment which can lead to extinction.

Keywords: affixation, contrastive study, Ipe, morphology, pedagogy, Yoruba

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Authors: Takahiro Nishigaki, Takashi Onoda

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In recent years, the number of document data has been increasing since the spread of the Internet. Many methods have been studied for extracting topics from large document data. We proposed Independent Topic Analysis (ITA) to extract topics independent of each other from large document data such as newspaper data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis. The topic represented by ITA is represented by a set of words. However, the set of words is quite different from the topics the user imagines. For example, the top five words with high independence of a topic are as follows. Topic1 = {"scor", "game", "lead", "quarter", "rebound"}. This Topic 1 is considered to represent the topic of "SPORTS". This topic name "SPORTS" has to be attached by the user. ITA cannot name topics. Therefore, in this research, we propose a method to obtain topics easy for people to understand by using the web search engine, topics given by the set of words given by independent topic analysis. In particular, we search a set of topical words, and the title of the homepage of the search result is taken as the topic name. And we also use the proposed method for some data and verify its effectiveness.

Keywords: independent topic analysis, topic extraction, topic naming, web search engine

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Authors: Omenogor, Happy Dumbi

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This paper examines the areas of convergence and divergence between English and Ųkwųanį (a language in Nigeria) vowel systems with particular emphasis on the front vowels. It specifies areas of difficulty for the average Ųkwųanį users of English and Ųkwųanį L1 users of English as a second language. The paper explains the nature of contrastive analysis, the geographical locations where Ųkwųanį is spoken as mother tongue as well as English and Ųkwųanį front vowels. The principles of establishing phonemes, minimal pairs in Ųkwųanį as well as the vowel charts in both languages are among the issues highlighted in this paper.

Keywords: convergence, divergence, English, Ukwųanį

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Authors: B. J. Sandesh, Saurabha Jirgi, S. Vidya, Prakash Eljer, Gowri Srinivasa

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In this paper, we propose a framework to help users to search and retrieve the portions in the lecture video of their interest. This is achieved by temporally segmenting and indexing the lecture video using the topic keywords. We use transcribed text from the video and documents relevant to the video topic extracted from the web for this purpose. The keywords for indexing are found by applying the non-negative matrix factorization (NMF) topic modeling techniques on the web documents. Our proposed technique first creates indices on the transcribed documents using the topic keywords, and these are mapped to the video to find the start and end time of the portions of the video for a particular topic. This time information is stored in the index table along with the topic keyword which is used to retrieve the specific portions of the video for the query provided by the users.

Keywords: video indexing and retrieval, lecture videos, content based video search, multimodal indexing

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Authors: Chris Adetuyi, Adeola Adeniran

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The concept of meaning is a complex one in language study when cultural features are added. This is mandatory because language cannot be completely separated from the culture in which case language and culture complement each other. When there are two varieties of a language in a society, i.e. two varieties functioning side by side in a speech community, there is a tendency to view one of the varieties with each other. There is, therefore, the need to make a linguistic comparative study of varieties of such languages. In this paper, a semantic contrastive study is made between Standard British English (SBE) and Nigerian English (NB). The semantic study is limited to aspects of semantics: semantic extension (Kinship terms, metaphors), semantic shift (lexical items considered are ‘drop’ ‘befriend’ ‘dowry’ and escort) acronyms (NEPA, JAMB, NTA) linguistic borrowing or loan words (Seriki, Agbada, Eba, Dodo, Iroko) coinages (long leg, bush meat; bottom power and juju). In the study of these aspects of semantics of SBE and NE lexical terms, conservative statements are made, problems areas and hierarchy of difficulties are highlighted with a view to bringing out areas of differences are highlighted in this paper are concerned. The study will also serve as a guide in further contrastive studies in some other area of languages.

Keywords: aspect, British, English, Nigeria, semantics

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Authors: Jun Gao

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This paper combines the corpus-based and contrastive approaches, seeking to provide a systematic account of cataphora in English and Chinese natural conversations. Based on spoken corpus data, the first part of the paper examines a range of characteristics of cataphora in the two languages, including frequency of occurrence, patterns, and syntactic features. On the basis of this exploration, cataphora in the two languages are contrasted in a structured way. The analysis shows that English and Chinese share a similar distribution of cataphora in natural conversations in terms of frequency of occurrence, with repeat identification cataphora higher than first mention cataphora and intra-sentential cataphora much higher than inter-sentential cataphora. In terms of patterns, three types are identified in English, i.e. P+N, Ø+N, and it+Clause, while in Chinese, two types are identified, i.e., P+N and Ø+N. English and Chinese are similar in terms of syntactic features, i.e., cataphor and postcedent in the intra-sentential cataphora mainly occur in the initial subject position of the same clause, with postcedent immediately followed or delayed, and cataphor and postcedent are mostly in adjacent sentences in inter-sentential cataphora. In the second part of the paper, the motivations of cataphora are investigated. It is found that cataphora is primarily motivated by the speaker and hearer’s different knowledge states with regard to the referent. Other factors are also involved, such as interference, word search, and the tension between the principles of Economy and Clarity.

Keywords: cataphora, contrastive study, motivation, pattern, syntactic features

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Authors: Maria Zinnia Bardas Hoffmann

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Contrastive Analysis (CA) is the systematic comparison between two languages. It stems from the notion that errors are caused by interference of the L1 system in the acquisition process of an L2. CA represents a useful tool to understand the nature of learning and acquisition. Also, this particular method promises a path to un-derstand the nature of underlying cognitive processes, even when other factors such as intrinsic motivation and teaching strategies were found to best explain student’s problems in acquisition. CA study is justified not only from the need to get a deeper understanding of the nature of SLA, but as an invaluable source to provide clues, at a cognitive level, for those general processes involved in rule formation and abstract thought. It is relevant for cross disciplinary studies and the fields of Computational Thought, Natural Language processing, Applied Linguistics, Cognitive Linguistics and Math Theory. That being said, this paper intends to address here as well its own set of constraints and limitations. Finally, this paper: (a) aims at identifying some of the difficulties students may find in their learning process due to the nature of their specific variety of L1, Rio de la Plata Spanish (RPS), (b) represents an attempt to discuss the necessity for specific models to approach CA.

Keywords: second language acquisition, applied linguistics, contrastive analysis, applied contrastive analysis English language department, meta-linguistic rules, cross-linguistics studies, computational thought, natural language processing

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Authors: Geovana Soncin, Larissa Berti

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Some aspects of prosody acquisition remain still unclear, especially regarding atypical speech development processes. This work deals with prosody acquisition and its implications for clinical purposes. Therefore, we analyze speech samples produced by adult speakers, children in typical language development, and children with phonological disorders. Phonological disorder comprises deviating manifestations characterized by inconsistencies in the phonological representation of a linguistic system under acquisition. The clinical assessment is performed mostly based on contrasts whose manifestations occur in the segmental level of a phonological system. Prosodic organization of spoken utterances is not included in the standard assessment. However, assuming that prosody is part of the phonological system, it was hypothesized that children with Phonological Disorders could present inconsistencies that also occur at a prosodic level. Based on this hypothesis, the paper aims to analyze contrastive focus marking in the speech of children with Phonological Disorders in comparison with the speech of children under Typical Language Development and adults. The participants of all groups were native speakers of Brazilian Portuguese. The investigation was designed in such a way as to identify differences and similarities among the groups that could be interpreted as clues of normal or deviant processes of prosody acquisition. Contrastive focus in Brazilian Portuguese is marked by increasing duration, f0, and intensity on the focused element as well as by a particular type of pitch accent (L*+H). Thirty-nine subjects participated, thirteen from each group. Acoustic analysis was performed, considering duration, intensity, and intonation as parameters. Children with PD were recruited in sessions from a service provided by Speech-Language Pathology Therapy; children in TD, paired in age and sex with the first group, were recruited in a regular school; and 20-24 years old adults were recruited from a University class. In a game prepared to elicit focused sentences, all of them produced the sentence “Girls love red dress,” marking focus on different syntactic positions: subject, verb, and object. Results showed that adults, children in typical language development, and children with Phonological Disorders marked contrastive focus differently: typical children used all parameters like adults do; however, in comparison with them, they exaggerated duration and, in the opposite direction, they did not increase f0 in a sufficient magnitude as adults; children with Phonological Disorder presented inconsistencies in duration, not increasing it in some syntactic positions, and also in intonation, not producing the representative pitch accent of contrastive focus. The results suggest prosody is also affected by phonological disorder and give clues of developmental processes of prosody acquisition.

Keywords: Brazilian Portuguese, contrastive focus, phonological disorder, prosody acquisition

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Authors: Usama Shahid

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Be it written documents, news columns, or students' essays, verifying the content can be a time-consuming task. Apart from the spelling and grammar mistakes, the proofreader is also supposed to verify whether the content included in the essay or document is relevant or not. The irrelevant content in any document or essay is referred to as off-topic text and in this paper, we will address the problem of off-topic text detection from a document using machine learning techniques. Our study aims to identify the off-topic content from a document using Echo state network model and we will also compare data with other models. The previous study uses Convolutional Neural Networks and TFIDF to detect off-topic text. We will rearrange the existing datasets and take new classifiers along with new word embeddings and implement them on existing and new datasets in order to compare the results with the previously existing CNN model.

Keywords: off topic, text detection, eco state network, machine learning

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Authors: Jose Marie E. Ocdenaria, Riceli C. Mendoza

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Culturally, languages meet, merge, share, exchange, appropriate, donate, and divide in and to and from each other. Further, this type of recurrence manifests in East Asian cultures, where language influence diffuses across geographical proximities. Historically, China has notable impacts on Japan’s culture. For instance, Japanese borrowed words from China and their way of reading and writing. This qualitative and descriptive employing contrastive analysis study addressed the true and false cognates of Japanese-Philippine languages and Chinese-Philippine languages. It involved a rich collection of data from various sources like textual pieces of evidence or corpora to gain a deeper understanding of true and false cognates between L1 and L2. Cognates of Japanese-Philippine languages and Chinese-Philippine languages were analyzed contrastively according to orthography, phonology, and semantics. The words presented were the roots; however, derivatives, reduplications, and variants of stress were included when they shed emphases on the comparison. The basis of grouping the cognates was its phonetic-semantic resemblance. Based on the analysis, it revealed that there are words which may have several types of lexical relationship. Further, the study revealed that the Japanese language has more false cognates in the Philippine languages, particularly in Tagalog and Cebuano. On the other hand, there are more true cognates of Chinese in Tagalog. It is the hope of this study to provide a significant contribution to a diverse audience. These include the teachers and learners of foreign languages such as Japanese and Chinese, future researchers and investigators, applied linguists, curricular theorists, community, and publishers.

Keywords: Contrastive Analysis, Japanese, Chinese and Philippine languages, Qualitative and descriptive study, True and False Cognates

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Authors: Melanie Kerschner

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Language is our main means of social interaction. News journalism, especially opinion discourse, holds a powerful position in this context. Editorials can be regarded as encounters of different, partially contradictory relationships between discourse participants constructed through the editorial voice. Their primary goal is to shape public opinion by commenting on events already addressed by other journalistic genres in the given newspaper. In doing so, the author tries to establish a consensus over the negotiated matter (i.e. the news event) with the reader. At the same time, he/she claims authority over the “correct” description and evaluation of an event. Yet, how can the relationship and the interaction between the discourse participants, i.e. the journalist, the reader and the news actors represented in the editorial, be best visualized and studied from a cross-cultural perspective? The present research project attempts to give insights into the role of (media) culture in British, Italian and German editorials. For this purpose the presenter will propose a basic framework: the so called “pyramid of discourse participants”, comprising the author, the reader, two types of news actors and the semantic macro-structure (as meta-level of analysis). Based on this framework, the following questions will be addressed: • Which strategies does the author employ to persuade the reader and to prompt him to give his opinion (in the comment section)? • In which ways (and with which linguistic tools) is editorial opinion expressed? • Does the author use adjectives, adverbials and modal verbs to evaluate news actors, their actions and the current state of affairs or does he/she prefer nominal labels? • Which influence do language choice and the related media culture have on the representation of news events in editorials? • In how far does the social context of a given media culture influence the amount of criticism and the way it is mediated so that it is still culturally-acceptable? The following culture-contrastive study shall examine 45 editorials (i.e. 15 per media culture) from six national quality papers that are similar in distribution, importance and the kind of envisaged readership to make valuable conclusions about culturally-motivated similarities and differences in the coverage and assessment of news events. The thematic orientation of the editorials will be the NSA scandal and the reactions of various countries, as this topic was and still is relevant to each of the three media cultures. Starting out from the “pyramid of discourse participants” as underlying framework, eight different criteria will be assigned to the individual discourse participants in the micro-analysis of the editorials. For the purpose of illustration, a single criterion, referring to the salience of authorial opinion, will be selected to demonstrate how the pyramid of discourse participants can be applied as a basis for empirical analysis. Extracts from the corpus shall furthermore enhance the understanding.

Keywords: Micro-analysis of editorials, culture-contrastive research, media culture, interaction between discourse participants, evaluation

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Authors: Yufen Qin

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Topic-to-Essay generation is a challenging task in Natural language processing, which aims to generate novel, diverse, and topic-related text based on user input. Previous research has overlooked the generation of articles under the constraints of event elements, resulting in issues such as incomplete event elements and logical inconsistencies in the generated results. To fill this gap, this paper proposes an event-constrained approach for a topic-to-essay generation that enforces the completeness of event elements during the generation process. Additionally, a language model is employed to verify the logical consistency of the generated results. Experimental results demonstrate that the proposed model achieves a better BLEU-2 score and performs better than the baseline in terms of subjective evaluation on a real dataset, indicating its capability to generate higher-quality topic-related text.

Keywords: event element, language model, natural language processing, topic-to-essay generation.

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Authors: Shashank Bhatnagar, W. Wilfred Godfrey

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We develop in this paper, an approach to find the trendy topic, which not only considers the user-topic interaction but also considers the community, in which user belongs. This method modifies the previous approach of user-topic interaction to user-community-topic interaction with better speed-up in the range of [1.1-3]. We assume that trend detection in a social network is dependent on two things. The one is, broadcast of messages in social network governed by self-exciting point process, namely called Hawkes process and the second is, Community Rank. The influencer node links to others in the community and decides the community rank based on its PageRank and the number of users links to that community. The community rank decides the influence of one community over the other. Hence, the Hawkes process with the kernel of user-community-topic decides the trendy topic disseminated into the social network.

Keywords: community detection, community rank, Hawkes process, influencer node, pagerank, trend detection

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Authors: Phumelele Kubheka, Pius Owolawi, Gbolahan Aiyetoro

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Twitter is one of the most popular social media platforms where users can share their opinions on different subjects. As of 2010, The Twitter platform generates more than 12 Terabytes of data daily, ~ 4.3 petabytes in a single year. For this reason, Twitter is a great source for big mining data. Many industries such as Telecommunication companies can leverage the availability of Twitter data to better understand their markets and make an appropriate business decision. This study performs topic modeling on Twitter data using Latent Dirichlet Allocation (LDA). The obtained results are benchmarked with another topic modeling technique, Latent Semantic Indexing (LSI). The study aims to retrieve topics on a Twitter dataset containing user tweets on South African Telcos. Results from this study show that LSI is much faster than LDA. However, LDA yields better results with higher topic coherence by 8% for the best-performing model represented in Table 1. A higher topic coherence score indicates better performance of the model.

Keywords: big data, latent Dirichlet allocation, latent semantic indexing, telco, topic modeling, twitter

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Authors: Wujian Han

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In the process of human interaction and communication, speech act verbs are considered to be the most active component and the main means for information transmission, and are also taken as an indication of the structure of linguistic behavior. The theoretical value and practical significance of such everyday built-in metalanguage have long been recognized. This paper, which is part of a bigger study, is aimed to provide useful insights for a more precise and systematic application to speech act verbs translation between English and Chinese, especially with regard to the degree to which generic integrity is maintained in the practice of translation of legal documents. In this study, the corpus, i.e. Chinese legal texts and their English translations, English legal texts, ordinary Chinese texts, and ordinary English texts, serve as a testing ground for examining contrastively the usage of English and Chinese directive speech act verbs in legal genre. The scope of this paper is relatively wide and essentially covers all directive speech act verbs which are used in ordinary English and Chinese, such as order, command, request, prohibit, threat, advice, warn and permit. The researcher, by combining the corpus methodology with a contrastive perspective, explored a range of characteristics of English and Chinese directive speech act verbs including their semantic, syntactic and pragmatic features, and then contrasted them in a structured way. It has been found that there are similarities between English and Chinese directive speech act verbs in legal genre, such as similar semantic components between English speech act verbs and their translation equivalents in Chinese, formal and accurate usage of English and Chinese directive speech act verbs in legal contexts. But notable differences have been identified in areas of difference between their usage in the original Chinese and English legal texts such as valency patterns and frequency of occurrences. For example, the subjects of some directive speech act verbs are very frequently omitted in Chinese legal texts, but this is not the case in English legal texts. One of the practicable methods to achieve adequacy and conciseness in speech act verb translation from Chinese into English in legal genre is to repeat the subjects or the message with discrepancy, and vice versa. In addition, translation effects such as overuse and underuse of certain directive speech act verbs are also found in the translated English texts compared to the original English texts. Legal texts constitute a particularly valuable material for speech act verb study. Building up such a contrastive picture of the Chinese and English speech act verbs in legal language would yield results of value and interest to legal translators and students of language for legal purposes and have practical application to legal translation between English and Chinese.

Keywords: contrastive analysis, corpus-based, directive speech act verbs, legal texts, translation between English and Chinese

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Authors: Rui Yin, Haojie Wang, Xun Li

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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then, the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. We also explore contrastive learning as a method for training domain-adapted dense retrievers and show that it leads to strong performance in various retrieval settings. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, contrastive learning, unsupervised training

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Authors: Gheida J. Shahrour, Martin J. Russell

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The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to their culture. We arranged each group into pairs and each pair communicated with each other about different topics. A state-of-art recognition system is applied to the problems of person, culture, and topic recognition. We borrowed modeling, classification, and normalization techniques from speech recognition. We used Gaussian Mixture Modeling (GMM) as the main technique for building our three systems, obtaining 77.78%, 55.47%, and 39.06% from the person, culture, and topic recognition systems respectively. In addition, we combined the above GMM systems with Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and 40.63% accuracy for person, culture, and topic recognition respectively. Although direct comparison among these three recognition systems is difficult, it seems that our person recognition system performs best for both GMM and GMM-SVM, suggesting that inter-subject differences (i.e. subject’s personality traits) are a major source of variation. When removing these traits from culture and topic recognition systems using the Nuisance Attribute Projection (NAP) and the Intersession Variability Compensation (ISVC) techniques, we obtained 73.44% and 46.09% accuracy from culture and topic recognition systems respectively.

Keywords: person recognition, topic recognition, culture recognition, 3D body movement signals, variability compensation

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Authors: Federica Floridi

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The long tradition of contrastive idiom research has essentially been focusing on three domains: the comparison of structural types of idioms (e.g. verbal idioms, idioms with noun-phrase structure, etc.), the description of idioms belonging to the same thematic groups (Sachgruppen), the identification of different types of cross-linguistic equivalents (i.e. full equivalents, partial equivalents, phraseological parallels, non-equivalents). The diastratic, diachronic and diatopic aspects of the compared idioms, as well as their syntactic, pragmatic and semantic properties, have been rather ignored. Corpora (both monolingual and parallel) give the opportunity to investigate the actual use of correlating idioms in authentic texts of L1 and L2. Adopting the corpus-based approach, it is possible to draw attention to the frequency of occurrence of idioms, their syntactic embedding, their potential syntactic transformations (e.g., nominalization, passivization, relativization, etc.), their combinatorial possibilities, the variations of their lexical structure, their connotations in terms of stylistic markedness or register. This paper aims to present the results of a contrastive analysis of Russian and Italian idioms referring to the concepts of ‘beginning’ and ‘end’, that has been carried out by using the Russian National Corpus and the ‘La Repubblica’ corpus. Beyond the digital corpora, bilingual dictionaries, like Skvorcova - Majzel’, Dobrovol’skaja, Kovalev, Čerdanceva, as well as monolingual resources, have been consulted. The study has shown that many of the idioms that have been traditionally indicated as cross-linguistic equivalents on bilingual dictionaries cannot be considered correspondents. The findings demonstrate that even those idioms, that are formally identical in Russian and Italian and are presumably derived from the same source (e.g., conceptual metaphor, Bible, classical mythology, World literature), exhibit differences regarding usage. The ultimate purpose of this article is to highlight that it is necessary to review and improve the existing bilingual dictionaries considering the empirical data collected in corpora. The materials gathered in this research can contribute to this sense.

Keywords: corpora, cross-linguistic equivalence, idioms, Italian, Russian

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Authors: Sidi Yang, Haiyi Zhang

Abstract:

Twitter is a microblogging platform, where millions of users daily share their attitudes, views, and opinions. Using a probabilistic Latent Dirichlet Allocation (LDA) topic model to discern the most popular topics in the Twitter data is an effective way to analyze a large set of tweets to find a set of topics in a computationally efficient manner. Sentiment analysis provides an effective method to show the emotions and sentiments found in each tweet and an efficient way to summarize the results in a manner that is clearly understood. The primary goal of this paper is to explore text mining, extract and analyze useful information from unstructured text using two approaches: LDA topic modelling and sentiment analysis by examining Twitter plain text data in English. These two methods allow people to dig data more effectively and efficiently. LDA topic model and sentiment analysis can also be applied to provide insight views in business and scientific fields.

Keywords: text mining, Twitter, topic model, sentiment analysis

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Authors: Tian Zhang

Abstract:

Unsupervised object segmentation aims at segmenting objects in sequential images and obtaining the mask of each object without any manual intervention. Unsupervised segmentation remains a challenging task due to the lack of prior knowledge about these objects. Previous methods often require manually specifying the action of each object, which is often difficult to obtain. Instead, this paper does not need action information of objects and automatically learns the actions and relations among objects from the structured environment. To obtain the object segmentation of sequential images, the relationships between objects and images are extracted to infer the action and interaction of objects based on the multi-head attention mechanism. Three types of objects’ relationships in the object segmentation task are proposed: the relationship between objects in the same frame, the relationship between objects in two frames, and the relationship between objects and historical information. Based on these relationships, the proposed model (1) is effective in multiple objects segmentation tasks, (2) just needs images as input, and (3) produces better segmentation results as more relationships are considered. The experimental results on multiple datasets show that this paper’s method achieves state-of-art performance. The quantitative and qualitative analyses of the result are conducted. The proposed method could be easily extended to other similar applications.

Keywords: unsupervised object segmentation, attention mechanism, contrastive learning, structured environment

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Authors: Jianhua Wang

Abstract:

To obtain key information quickly from long texts on small screens of mobile devices, sight-interpreters need to establish optimized summarization model for fast information retrieval. Four summarization models based on previous studies were studied including title+key words (TKW), title+topic sentences (TTS), key words+topic sentences (KWTS) and title+key words+topic sentences (TKWTS). Psychological experiments were conducted on the four models for three different genres of interpreting texts to establish the optimized summarization model for sight-interpreters. This empirical study shows that the optimized summarization model for sight-interpreters to quickly grasp the key information of the texts they interpret is title+key words (TKW) for cultural texts, title+key words+topic sentences (TKWTS) for economic texts and topic sentences+key words (TSKW) for political texts.

Keywords: different genres, mobile screens, optimized summarization models, sight-interpreters

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Authors: Moulana Mohammed

Abstract:

Topic models are widely used in building clusters of documents for more than a decade, yet problems occurring in choosing optimal number of topics. The main problem is the lack of a stable metric of the quality of topics obtained during the construction of topic models. The authors analyzed from previous works, most of the models used in determining the number of topics are non-parametric and quality of topics determined by using perplexity and coherence measures and concluded that they are not applicable in solving this problem. In this paper, we used the parametric method, which is an extension of the traditional topic model with visual access tendency for visualization of the number of topics (clusters) to complement clustering and to choose optimal number of topics based on results of cluster validity indices. Developed hybrid topic models are demonstrated with different Twitter datasets on various topics in obtaining the optimal number of topics and in measuring the quality of clusters. The experimental results showed that the Visual Non-negative Matrix Factorization (VNMF) topic model performs well in determining the optimal number of topics with interactive visualization and in performance measure of the quality of clusters with validity indices.

Keywords: interactive visualization, visual mon-negative matrix factorization model, optimal number of topics, cluster validity indices, Twitter data clustering

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Authors: Maryam Heidari, James H. Jones Jr.

Abstract:

Millions of online posts about different topics and products are shared on popular social media platforms. One use of this content is to provide crowd-sourced information about a specific topic, event or product. However, this use raises an important question: what percentage of information available through these services is trustworthy? In particular, might some of this information be generated by a machine, i.e., a bot, instead of a human? Bots can be, and often are, purposely designed to generate enough volume to skew an apparent trend or position on a topic, yet the consumer of such content cannot easily distinguish a bot post from a human post. In this paper, we introduce a model for social media bot detection which uses Bidirectional Encoder Representations from Transformers (Google Bert) for sentiment classification of tweets to identify topic-independent features. Our use of a Natural Language Processing approach to derive topic-independent features for our new bot detection model distinguishes this work from previous bot detection models. We achieve 94\% accuracy classifying the contents of data as generated by a bot or a human, where the most accurate prior work achieved accuracy of 92\%.

Keywords: bot detection, natural language processing, neural network, social media

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Authors: Hayoung Cho, Gabi Cho

Abstract:

In response to the continuing increase of demands for living environment safety, the Korean government has established and implemented various environmental health policies and set a high priority to the related R&D. However, the level of related technologies such as environmental risk assessment are still relatively low, and there is a need for detailed investment strategies in the field of environmental health research. As scientific research papers can give valuable implications on the development of a certain field, this study analyzed the global research trends in the field of environmental health over the past 10 years (2005~2015). Research topics were extracted from abstracts of the collected SCI papers using topic modeling to study the changes in research trends and discover emerging technologies. The method of topic modeling can improve the traditional bibliometric approach and provide a more comprehensive review of the global research development. The results of this study are expected to help provide insights for effective policy making and R&D investment direction.

Keywords: environmental health, paper analysis, research trends, topic modeling

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