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以发送短信和打电话方式为主的手机交往,日益渗透到人们日常生活,成为现代社会的生活方式。本文以“沿海发达城市市民新媒介接触与使用”课题数据为实证研究的基础,聚焦市民的短信使用行为。经过SPSS软件的统计、分析表明,人口学变量(性别、年龄、文化收入、职业、收入和支出)与手机使用程度有显著差异,短信交往行为与短信发送对象、短信发送者偏好态度存在相关性。基于此,本文使用OLS回归分析方法,分别对手机使用程度和情感类短信交往的影响因素回归模型做了探索性研究。OLS线性回归模型发现:第一,性别、年龄、文化程度、职业(“经理人员”、“私营企业主”、“军人”、“企业管理技术人员”“个体工商户”“企业工人商业服务人员”和“学生”)、收入和支出的人口学变量会影响手机的使用程度;该模型的解释度为29.7%。第二,影响人们是否会发送短信情感交流的变量有:性别、年龄、收入和职业(“事业单位管理技术人员科教文卫工作者”、“企业管理技术人员”和“学生”)的人口学变量;短信联系人为“亲人”、“同事或同学”和“其他普通朋友”的关系变量;对语音和短信单一偏好的态度变量。该模型的解释度为27.6%。综合这两个模型,本研究对未来的手机使用研究提出归化研究和经济变量两个建议。
To send text messages and phone-based mobile phone contacts, increasingly penetration of people’s daily lives, become a modern society’s way of life. Based on the empirical research of the subject data of “New Media Contact and Use in Citizens of Coastal Developed Cities”, this paper focuses on citizen SMS usage. Through the SPSS software statistics, the analysis shows that the demographic variables (gender, age, cultural income, occupation, income and expenditure) have significant differences with the degree of use of mobile phones, SMS interaction behavior and the SMS sent to the object, the relevance of SMS sender attitudes . Based on this, this paper uses the OLS regression analysis method, respectively, to explore the degree of use of mobile phones and emotional factors SMS regression model of influencing factors. OLS linear regression model found that: First, gender, age, education level, occupation (“manager”, “private entrepreneur ”, “soldier ”, “enterprise management technician ” The demographic variables of income and expenditure affect the use of mobile phones; the interpretation of the model is 29.7%. Second, the variables affecting the emotional exchange of people sending text messages include: gender, age, income, and occupation (“Science and Technology Workers in Health Care Workers,” “Business Management Technicians,” and “Students” “) Demographic variables; SMS contacts as ” relatives “, ” colleagues or classmates “and ” other common friends "relationship variables; voice and text messages on a single preferred attitude variables. The model’s interpretation is 27.6%. Combining these two models, this study proposes two suggestions for naturalization research and economic variables for the future research on cellphone use.