發(fā)布時間：2018-05-10 08:29

  本文選題：網(wǎng)絡(luò)依賴 + 文本分析�。� 參考：《華中師范大學(xué)》2017年碩士論文

【摘要】：隨著互聯(lián)網(wǎng)的普及與飛速發(fā)展,對網(wǎng)絡(luò)的過度使用現(xiàn)象得到了學(xué)界的普遍關(guān)注。許多研究者從認知功能缺陷、情緒功能障礙等不同角度對網(wǎng)絡(luò)成癮行為進行了研究,普遍認為網(wǎng)絡(luò)成癮個體具有對現(xiàn)實生活適應(yīng)不良的表現(xiàn)特征。目前對網(wǎng)絡(luò)成癮行為的研究,主要是通過觀察個體線下的行為表現(xiàn)來分析并甄別其網(wǎng)絡(luò)使用程度是否異常,缺乏對網(wǎng)絡(luò)成癮者線上行為特征的實證研究。本研究通過誘發(fā)個體的特定情緒狀態(tài)、選取不同類型的網(wǎng)絡(luò)線索,結(jié)合文本分析技術(shù)來考察高、低程度網(wǎng)絡(luò)依賴個體的在線語言用詞特征,為今后實現(xiàn)在線動態(tài)地甄別網(wǎng)絡(luò)成癮行為提供參考依據(jù)。研究一通過誘發(fā)個體的特定情緒誘發(fā),分別考察高、低程度的網(wǎng)絡(luò)依賴者在積極-消極情緒狀態(tài)下、面對積極-消極閱讀文本時其在線語言用詞的差異。結(jié)果表明,個體的情緒狀態(tài)對高程度網(wǎng)絡(luò)依賴個體的線上語言用詞的影響甚微,閱讀文本的情緒屬性對其影響顯著。同時,網(wǎng)絡(luò)活動可以改善個體的負面情緒體驗,特別是對高程度網(wǎng)絡(luò)依賴的使用者而言,他們在進行網(wǎng)絡(luò)活動可以得到更大程度的情緒調(diào)節(jié)。研究二通過模擬社交媒體平臺常見的圖文閱讀模式,分別進行積極和消極文本評論實驗,考察了高、低程度網(wǎng)絡(luò)依賴者面對積極、消極閱讀文本與不同的配圖類型時的線上語言用詞線索。結(jié)果表明,配圖類型能夠影響高程度網(wǎng)絡(luò)依賴者的線上語言用詞;尤其是卡通表情這一與互聯(lián)網(wǎng)高度關(guān)聯(lián)的線索,高程度網(wǎng)絡(luò)依賴的個體對卡通表情配圖更加熟悉,若閱讀文本結(jié)合了卡通表情配圖,則會阻礙他們對積極文本信息的再次評估和喚起對消極文本信息的重新評價。同時卡通表情配圖的存在,會降低高程度網(wǎng)絡(luò)依賴的個體對文本信息的負面感受,加重低程度網(wǎng)絡(luò)依賴的個體對消極文本信息的負面情緒體驗。綜上所述,高程度網(wǎng)絡(luò)依賴個體的線上行為表現(xiàn)與現(xiàn)實生活中有所差異。今后研究可利用更高級的數(shù)據(jù)挖掘技術(shù),通過先分析主題文本的情緒屬性與配圖類型、后探索基于主題的評論文本語言特征,來實現(xiàn)在線動態(tài)地甄別網(wǎng)絡(luò)成癮行為。
[Abstract]:With the popularity and rapid development of the Internet, the phenomenon of excessive use of the network has received widespread attention. Many researchers have studied the behavior of Internet addiction from different angles such as cognitive impairment emotional dysfunction and so on. It is generally believed that the individual of Internet addiction has the characteristics of poor adaptation to real life. At present, the research on Internet addiction behavior is mainly to analyze and identify whether the degree of internet use is abnormal or not by observing the behavior of individuals below the line, and lack of empirical research on the online behavior characteristics of Internet addicts. In this study, the specific emotional state of individuals was induced, different types of network cues were selected, and text analysis techniques were used to investigate the online language features of individuals with high and low degree of network dependence. To provide a reference for the realization of online dynamic discrimination of Internet addiction behavior in the future. In the first study, we investigated the differences of online language words of high and low degree network dependent people in the positive and negative emotional state in the face of the positive and negative reading text by inducing the specific emotion of the individual. The results show that the emotional state of the individual has little effect on the online language words of the individual with high degree of network dependence, while the emotional attribute of the reading text has a significant effect on it. At the same time, Internet activities can improve the negative emotional experience of individuals, especially for users with high degree of network dependence, they can get a greater degree of emotional adjustment in the process of online activities. In the second study, by simulating the common pattern of text reading on social media platform, the positive and negative text review experiments were carried out respectively, and the high and low degree of network dependence were investigated to face the positive. Negative reading text with different map types when online language use cues. The results show that the type of matching images can affect the online language words of the high degree network dependent people, especially cartoon expression, which is a highly related clue to the Internet, and the individuals with high degree of network dependence are more familiar with the cartoon facial expression matching. If the reading text combines cartoon facial expression matching, it will prevent them from re-evaluating the positive text information and evoking the re-evaluation of the negative text information. At the same time, the existence of cartoon facial expression matching images will reduce the negative feelings of individuals with high degree of network dependence on text information, and aggravate the negative emotional experience of individuals with low degree of network dependence on negative text information. To sum up, the online behavior of individuals with high degree of network dependence is different from that of real life. In the future, more advanced data mining techniques can be used to dynamically identify online addictive behaviors by analyzing the emotional attributes and matching graph types of topic texts, and then exploring the language features of subject based comments.
【學(xué)位授予單位】：華中師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：B845

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本文編號：1868584