Biterm topic model of social network users’ sentiment by integrating word co-occurrence by Qiuyang GU, Bao WU, Chunhua JU

“…With the increasing number of social network users in recent years,text-based user sentiment analysis technology has been widely concerned and applied.However,data sparsity and low accuracy often reduce the accuracy and speed of emotion recognition methods.The user emotion Biterm topic model (US-BTM) was proposed which could find user preference and emotional tendency from the text of specific places,so as to effectively use Biterm for topic modeling.The strategy of user aggregation to form pseudo-documents was used,and word pairs were created for the whole corpus to solve the problems of data sparsity and short text.Then the topic was studied through the lexical co-occurrence model,so as to infer the topic with abundant corps-level information,and the purpose of accurately predicting the user’s interest,preference and emotion to the specific scene was achieved by analyzing the lexical matching set in the comment corpus under the specific scene and the emotion of the corresponding topic.The experimental results show that the method proposed can accurately capture users’ emotional tendency and correctly reveal users’ preference,which can be widely used in social network content description,recommendation,social network user interest description,semantic analysis and other fields.…”
Get full text

Text steganography method based on automatic selection coding and dynamic word selection strategy by Hui LI, Jiali JIN, Shuyu JIN, Weijiao MA

“…A text steganography method based on automatic selection coding and dynamic word selection strategy was proposed for the inflexible text coding method and candidate word increasing number leading to the low quality of generated steganographic text.Steganographic translations was generated based on Transformer’s neural machine translation model.In generating steganographic translations, fixed-length coding and Huffman coding were used to establish the mapping relationship between candidate words and codewords, and dynamic word selection based on the probability difference threshold was achieved by calculating the probability difference percentage between steganographic words and normal words.Finally, the size of the two generated steganographic translations Sacrebleu was compared to realize the automatic selection of coding mode.The experimental results show that the proposed method can generate steganographic translations with high fluency and readability.When the embedding rate is 11.19%, the Sacrebleu of the steganographic translation reaches 10.53.…”
Get full text

The Power of Words: A Study of How Search Contents Can Affect Financial Decisions by Du Ni, Xingzhi Li, Zhi Xiao, Ke Gong

“…Therefore, this study was carried out to analyze the emotional meanings of 13,915 English words obtained from Google Trends and the profits gained from the US house market by automatic transactions and discovered that the emotional meanings of the search contents could modulate the financial decision with unsupervised machine learning methods.…”
Get full text

Structure and usage do not explain each other: an analysis of German word-initial clusters by Wiese Richard, Orzechowska Paula

“…The present study focuses on German word-initial consonant clusters and asks whether feature-based phonotactic preferences correlate with patterns of type and token frequencies in present-day usage. …”
Get full text

Corrigendum to “High on Cannabis and Calcineurin Inhibitors: A Word of Warning in an Era of Legalized Marijuana” by Naomi Hauser, Tanmay Sahai, Rocco Richards, Todd Roberts

Get full text

The effect of social media marketing, electronic word-of-mouth, brand image on purchase intention by Aldan Mutia Ramadhan, Heppy Millanyani

Subjects: Get full text

Pengaruh Kepercayaan Merek, Brand Ambassador dan Word of Mouth Terhadap Keputusan Pembelian by Vianandra Intan Puspanada, Suzy Widyasari

Subjects: Get full text

Affective polarization in a word: Open-ended and self-coded evaluations of partisan affect by Spencer Kiesel, Sharif Amlani

Get full text

Introducing an Unknown-Familiar one and a âNew Design for Word-Formation in Persian by وحید سبزیان‌پور

Subjects: Get full text

A Quantitative Study on Dream of the Red Chamber: Word-Length Distribution and Authorship Attribution by Yue Yu, Wei Liu, Ying Feng

“…This paper investigates the distribution characteristics of word lengths in the Dream of the Red Chamber (DRC), measured in terms of the number of syllables or characters. …”
Get full text

Drug-target binding affinity prediction based on power graph and word2vec by Jing Hu, Shuo Hu, Minghao Xia, Kangxing Zheng, Xiaolong Zhang

Subjects: Get full text

Affective polarization in a word: Open-ended and self-coded evaluations of partisan affect. by Spencer Kiesel, Sharif Amlani

“…Our measure asks respondents for one-word to describe voters in their party and the opposing party. …”
Get full text

His bundle pacing – a new word in technology of pacing and treatment of heart failure by Ya.V. Skybchyk, Ye.V. Zhytyns’kiy, О.М. Grytsay, V.О. Kuts, О.J. Zharinov

Get full text

Representing Irishness in Words and Images ; Erskine Nicol’s Illustrations of Tales of Irish Life and Character by Amélie Dochy

Get full text

A Few Words about the Hybrid Nature of Mawlid’s Text of the 18th Century by Alla Kozhinowa

“…There are a number of Arabic and Turkish words in the text. Regarding Slavonic words, it is difficult to determine their origin accurately due to genetic links of the languages. …”
Get full text

Articulatory-to-Acoustic Conversion Using BiLSTM-CNN Word-Attention-Based Method by Guofeng Ren, Guicheng Shao, Jianmei Fu

“…By considering the graphical representation of the articulators’ motion, this study combined Bidirectional Long Short-Term Memory (BiLSTM) with convolution neural network (CNN) and adopted the idea of word attention in Mandarin to extract semantic features. …”
Get full text

OPTIMIZING STUDENTS’ LOW FREQUENCY WORDS ACHIEVEMENT THROUGH IMPLEMENTING MODIFIED KEYWORD METHOD by Anjar Muttaqin

“…There are 21 low-frequency words to grasp in order to be able to understand two texts of English. …”
Get full text

The potential of artificial intelligence (AI) to improve electronic word-of-mouth's (eWOM) efficacy by Baltezarević Radoslav V., Kwiatek Piotr B.

Subjects: Get full text

Fixed Point Results in Fuzzy Strong Controlled Metric Spaces with an Application to the Domain Words by Aftab Hussain, Umar Ishtiaq, Hamed Al Sulami

Get full text

A Hybrid Contextual Embedding and Hierarchical Attention for Improving the Performance of Word Sense Disambiguation by Robbel Habtamu Yigzaw, Beakal Gizachew Assefa, Elefelious Getachew Belay

Subjects: Get full text