The Factor of Network Catchwords on the Construct of Public Sphere

This study analyzed the chatting records of the respondents and highlighted the network catchwords they have used in the contents. In this paper, the study investigated several individuals in a case study and chose network catchwords with the typical characteristics. In addition, network catchwords on construction motivation principles were collected as corpus. Therefore, this factor affects the construct of rural areas and smart communities in China.

X. F. Ma DOI: 10.4236/jss.2022.107003 28 Open Journal of Social Sciences but a complicated social phenomenon. Therefore, the transmission and use of a language partly reflect the collective psychological feature of the society, and sometimes depict the real cultural environment in a certain age. The research aiming at catchwords can hardly be unacceptable because the continuing study will record the changing of ages and the variation of languages. Nowadays, although we have reached a lot of achievements in catchword research, some other related problems are still unsolved. According to the literature review, no precise investigations aiming at individuals were done in this area, while a lot of analysis about the features, frequencies and vitality of catchwords were achieved based on the social surveys and corpus collection (Haythorn, 2002).
Government is the entity that fulfills the responsibilities to provide government information on the official website. Therefore, citizens' trust in government will exert a huge influence on their intentions to adopt e-government services.
Previous researches concluded that trust in government mainly includes two parts: government capability to fulfill its responsibilities and government integrity. As for government capability, governments need to have sufficient human resources as well as technology resources to ensure the steady and secure operation of their official websites. As for government integrity, an open, honest and accountable government, which releases information to the public in a timely manner and makes updates promptly in line with development of the situation, will gain more of the public's trust in e-government.
In this paper, the study investigated several individuals in a case study and chose network catchwords with the typical characteristics. In addition, network catchwords on construction motivation principles were collected as corpus.
This study analyzed the chatting records of the respondents and highlighted the network catchwords they have used in the contents.
After the collecting of chatting records, each respondent was interviewed in order to compare the frequency to their opinions and know their reasons for and attitudes towards using network catchwords.

Network Catchwords
The catchword defined in this study should have been already recorded by relia- The frequency of an event is the number of times the event occurred in a study. In this study, the frequency of catchwords used in the subjects' chatting records and the frequency of each category of catchwords that are constructed by different motivations were calculated according to the following formulas.
In the interview, the subjects answered ("Why do you use catchwords in social software chatting?") and presented their reasons of using catchwords. The reasons are summed up in entertainment, convenience in typing, following the trend.
According to Study, one of the basic features of catchwords is the novelty. The novelty of catchwords determines that users can be attracted by novel use of words and use a certain group of catchwords frequently in a certain period of time for entertainment.
Following the trend is another important reason in catchword using. In social software chatting, some catchwords are used when the user is not aware of the origin or the original meaning of the catchwords.
The data suggests that nearly 30% of the catchwords were used when the subjects were not aware of the original meanings or origins. The reason why the subjects could use those catchwords was that they learnt the way of use by imitating other users.
Compared with some previous studies about the frequency of use of catchwords, the data presents some similarity. For instance, in a survey provided by Allison Clair and Jim Mandler, 60% of the subjects thought that catchwords were very frequently used in their chatting. The similarity is that the subjective answers present higher frequencies in catchword using than the data collected from chatting records. The result implies that users may be less influenced by catchwords than they think (Clair & Mandler, 2019).
In previous study, the reasons were listed as: following the trend, convenience in communicating, entertainment, reflecting the age, convenience in typing, being curious and expressing complex meanings.
The reasons "following the trend", "entertainment" and "convenience in typing" were also mentioned. It implied that the three reasons might be the most important among the reasons.
In a survey of study, 200 respondents were surveyed about the attitude towards catchwords. 76.50% of the respondents indicated that they supported the use of catchwords in the survey 1 .
In the case study, all of the 5 subjects supported the use of catchwords and two of them provided their opinions of the standardization of catchwords. It implied that most of the students supported the use of catchwords, because catchwords have become an indispensible part in network communication.
This study calculated the frequency of catchwords and different categories of catchwords used on social software by subjects, and also collected the reasons and attitudes of the subjects towards using catchwords. 1) The frequency of catchwords by the subjects in social software chatting floats in a range from 0.84% to 2.58%, which is much lower than their subjective estimation.
2) The catchwords in this study were classified into 9 categories from four dimensions of construction motivations. The 9 categories are arranged from the highest frequency to the lowest frequency as: meaning shift, homophone, semantic polysemy, overlapping speech, borrowed words, acronyms, changing of connotations, special grammatical structures and affixation. By analyzing the data and the records of interview, the morphological motivation was found as the strongest motivation of catchwords in this study.
3) According to the interview, 3 reasons of the use of catchwords in social software chatting were found: entertainment, convenience in typing and following the trend.

4)
In the interview, all of the subjects supported the use of catchwords in social software chatting, while one subject reckoned positive standardization was necessary and another subject reckoned negative standardization was necessary.
As a case study, this study could only investigate and explore detailed data of certain subjects. Therefore, the data and analysis in this study can't be used for explaining or generalizing the use of network catchwords on social software chatting.
As a symbol system, language is the most important tool for communication and thought, and also a bond which keeps the normality of human society. So, the changing of society always affects the changing of language culture. In recent years, network catchwords have become a concern in language research (Inglis, 2016).

Rural Areas
During the process of social construction, the public sphere of cyberspace also pay more role, In 2021, China officially realized the second step of the "three-step" goal-to complete the building of a moderately prosperous society in all respects, and started a new journey of building a modern socialist country in all respects. In the year 2020 just passed, China's poverty alleviation task was successfully completed, and absolute poverty was eliminated historically. Among them, industrial poverty alleviation, as a "hematopoietic" poverty alleviation project, has played a huge role. However, this battle is far from over, and how to consolidate the results of this battle is particularly important. In the new journey towards economic development, rural areas still face many challenges in achieving sustainable development after poverty alleviation and gradually transiting to rural revitalization (Craig, 1999). The background in this paper, based on the re-

Smart Communities
It's also performed in smart communities of city. Chaoyang District has built a comprehensive smart community in eight streets.
This article takes an example of a community in the Chaoyang District of Beijing, analyzing the construction of the smart community and analyzing the lack of internal power such as residents' awareness and the lack of exogenous power such as hardware facilities in the construction of the smart community in this community. And make some suggestions. Through field research and information collation, it is found that smart communities are not simply a modern upgrade of the community. They should also combine their own conditions and take humanism seriously and promote the better development of smart communities.

Conflicts of Interest
The author declares no conflicts of interest regarding the publication of this paper.