Thesis

Conceptualizing and measuring human anxiety on the Internet

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Abstract

Since the 1990’s, the Internet has played a central role in our daily lives. The Internet is an integral part of our personal, business, family, research, entertainment, academic and social life. However, there are social implications in using the Internet that are dependent on categories such as gender, age, ethnicity and cultural attributes. This social aspect can play a detrimental role in the expression of human anxiety on the Internet. An anxiety is a complex phenomenon that requires further elaboration. Thus, the aim of this thesis is to investigate human anxiety, or specifically, whether Internet anxiety can be conceptualized and measured. This thesis utilizes literature, qualitative and quantitative research methodologies, and a triangulation validation approach to conceptualize and measure the Internet anxiety phenomenon. In particular, the aim is to explore anxiety levels of Internet participants to develop and validate an Internet anxiety scale based on earlier research on Internet anxiety. The results of the dissertation present a two phase study. In Phase I, a smaller set of studies were conducted with a limited sample size. In Phase II, the research topic was investigated using 385 participants. Based on a number of studies or experiments, the state-of-the-art discovered in this thesis is creation, design, and validation of two scales, the Self-Assessment Scale (SAS) and a Modified Internet Anxiety Scale (MIAS) for measuring users’ anxieties on the Internet. The result of this dissertation is a conceptualization and measurement of various types of Internet anxiety and measurement of affective feelings of users on the Internet. As a proof-of-concept of measuring Internet anxiety, this thesis describes the author’s implementation of three sets of tools: MyAnxiety, introducing Internet anxieties types; Intelligentia, for collecting Internet anxieties types; and MyIAControl tool, implemented as a browser plug-in, for measuring affective feelings of users on the Internet. Conclusions drawn from the results show that these empirically validated scales and tools might be useful for researchers and practitioners in understanding and measuring the Internet anxiety phenomenon further.

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... Since 1990's the Internet has played the dominant role in the advancement of the modern world [1,2]. With significant progress, also comes great responsibility for Artificial Intelligence (AI) and machine learning (ML) community. ...
... There is the enormous problem at stake academically: how can we optimize and strengthen the ML and data-driven platform for the social web that understands human emotions and feelings? To tackle this challenging problem, we have been developing the FeelCalc module [2,3] over several years. ...
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