Welcome to Scholar Publishing Group

International Journal of Social Sciences and Economic Management, 2021, 2(1); doi: 10.38007/IJSSEM.2021.020102.

Political Intention of Online Social Language in a Complex International Environment

Author(s)

Zijiang Zhu

Corresponding Author:
Zijiang Zhu
Affiliation(s)

South China Business College of Guangdong University of Foreign Studies, Guangdong, China

Abstract

As the development of the Internet has matured, people's social methods are gradually concentrated on virtual communication platforms. Because of this, the network language has also developed and expanded. In addition, as the Internet gradually integrated into people's lives, the enthusiasm of netizens to participate in online politics has also increased. The expression of online language is different from the traditional language rules, and it is highly accepted and spread quickly in online social networking. Internet language is basically a social phenomenon, so the form of network language will be changed by the change of social form. Based on the above background, the research content of this article is the political intent of the network social language in the complex international environment. This paper analyzes the current complex international relations environment and the formation and use of new online social language, discusses the intention of netizens to use online social language, and conducts experimental verification in the form of a questionnaire. The survey results show that netizens spend a lot of time in online life. Among the Chinese and foreign respondents, the proportion of Internet access within one hour per day accounts for 0.5% and 0.9%, respectively, less than 1%. More than ninety-nine percent of respondents have more than one hour of activity in the online environment every day. The online social language appears because netizens have formed a special online entertainment language that basically has no political intentions.

Keywords

International Environment, Social Networks, Online Language, Political Intentions, Questionnaire Survey

Cite This Paper

Zijiang Zhu. Political Intention of Online Social Language in a Complex International Environment. International Journal of Social Sciences and Economic Management (2021), Vol. 2, Issue 1: 11-21.  https://doi.org/10.38007/IJSSEM.2021.020102.

References

[1] Liu C, Zhang Y, Zhang P, et al. Neural Network Language Modeling Using an Improved Topic Distribution Feature. Dianzi Yu Xinxi Xuebao/journal of Electronics & Information Technology, 2018, 40(1):219-225.

[2] Chen X, Liu X, Wang Y, et al. Efficient Training and Evaluation of Recurrent Neural Network Language Models for Automatic Speech Recognition. IEEE/ACM Transactions on Audio Speech & Language Processing, 2016, 24(11):2146-2157.

[3] Sair H I, Yahyavi-Firouz-Abadi N, Calhoun V D, et al. Presurgical brain mapping of the language network in patients with brain tumors using resting-state fMRI: Comparison with task fMRI. Human Brain Mapping, 2016, 37(3):913-923.

[4] Wu Y C, Yin F, Liu C L. Improving handwritten Chinese text recognition using neural network language models and convolutional neural network shape models. PATTERN RECOGNITION, 2017, 2017(65):251-264.

[5] Fan Z, Chen S, Zha L, et al. A Text Clustering Approach of Chinese News Based on Neural Network Language Model. International Journal of Parallel Programming, 2016, 44(1):198-206.

[6] Lee H Y, Tseng B H, Wen T H, et al. Personalizing Recurrent-Neural-Network-Based Language Model by Social Network. IEEE/ACM Transactions on Audio Speech & Language Processing, 2017, 25(3):519-530.

[8] Oliveira V. Portuguese-language Network of Urban Morphology (PNUM): President's Report 2017/18. Urban Morphology, 2018, 22(2):167-167.

[9] Correia J. Sixth Conference of the Portuguese-language Network of Urban Morphology, Vit6ria, ES, Brazil, 24-25 August 2017. Urban Morphology, 2018, 22(1):83-83.

[10] Viana D L. Seventh Conference of the Portuguese-language Network of Urban Morphology (PNUM), Porto, Portugal, 18-19 July 2018. Urban Morphology, 2018, 22(2):139-139.

[11] Shuang S. Empire of Information: The Asia Foundation's Network and Chinese-Language Cultural Production in Hong Kong and Southeast Asia. American Quarterly, 2017, 69(3):589-610.

[12] Mendonca E M S. Fifth Conference of the Portuguese-language Network of Urban Morphology,Guimaräes, Portugal, 15-16 July 2016.. Urban Morphology, 2017, 21(1):28-28.

[13] Kipyatkova I S, Karpov A A. A study of neural network Russian language models for automatic continuous speech recognition systems. Automation & Remote Control, 2017, 78(5):858-867.

[14] Marat-Mendes T. Portuguese-language Network of Urban Morphology: President's Report. Urban morphology, 2016, 20(2):176-176.

[15] Albowarab M H, Zakaria N A, Abidin Z Z. Software Defined Network: Architecture and Programming Language Survey. International Journal of Pure and Applied Mathematics, 2018, 119(18):561-572.

[16] Joan A, Ting S H. Influence of Social Network on Language Use of Kejaman Speakers in Sarawak, Malaysia. Oceanic Linguistics, 2017, 56(1):22-41.

[17] Deena S, Hasan M, Doulaty M, et al. Recurrent Neural Network Language Model Adaptation for Multi-Genre Broadcast Speech Recognition and Alignment. IEEE/ACM Transactions on Audio Speech & Language Processing, 2019, 27(3):572-582.

[18] Koike S, Lee A. Spoken keyword detection using recurrent neural network language model. Journal of the Acoustical Society of America, 2016, 140(4):3116-3116.

[19] Kielar A, Deschamps T, Jokel R, et al. Functional reorganization of language networks for semantics and syntax in chronic stroke: Evidence from MEG. Human Brain Mapping, 2016, 37(8):2869-2893.

[20] Kielar A, Deschamps T, Jokel R, et al. Functional reorganization of language networks for semantics and syntax in chronic stroke: Evidence from MEG. Human Brain Mapping, 2016, 37(8):2869-2893.

[21] Ahmad, Farhan. Knowledge-Sharing Networks: Language Diversity, Its Causes, and Consequences. Knowledge and Process Management, 2017, 24(2):139-151.

[22] Tremblay A, Asp E, Johnson A, et al. What the Networks Tell us about Serial and Parallel Processing: An MEG Study of Language Networks and N-gram Frequency Effects in Overt Picture. The Mental Lexicon, 2016, 11(1):115-160.

[23] Celal VARIŞOĞLU Mehmet. The importance of strategies of social language learning and cooperative learning in the process of teaching Turkish as a foreign language. Educational Research & Reviews, 2016, 11(10):981-986.

[24] Hall J, Valdiviezo S. The Social Worker as Language Worker in a Multilingual World: Educating for Language Competence. Journal of Social Work Education, 2019(1):1-13.

[25] Tribur Z. Social network structure and language change in Amdo Tibetan. International Journal of the Sociology of Language, 2017, 2017(245):169-206.