The global development of the Internet has led companies to modify their strategies in search of new ways to increase their profitability. Additionally, to this new digital environment, the increased use of social networks and the Internet in general have become habits for consumers to the point that there are millions of devices connected to the Internet that are constantly generating new data-points about users behaviors and their habits and actions online.
As the use of these technologies has become habitual for users, it has also become commonplace for users to share information about their experiences, opinions or interests publicly via social networks and known as user-generated data (UGD). The possible sources of such user data are the questions that are explicit asked to users to provide details or alternatively, these data can be also inferred from the study of user actions online.
Therefore, UGD can be categorized into user-generated content (UGC, i.e. information that users know they are creating publicly) and user-generated behavior (UGB, i.e. information that is generated as a result of user actions). In looking at these types of data sources, several studies have analyzed how to collect UGD, how to analyze or identify patterns, or how to extract insights that can help companies improve their strategies and communications in digital environments . However, there is a gap in scientific research about the study of challenges, opportunities and consequences for user’s behavior online, that the study of UGD -including both UGC and UGB- can bring to the understanding of how they perform their behave online.
Consequently, understanding the behavior of online users has become a key piece for the development of internet-focused strategies in which UGD have become a key concept to understand how users behave in digital ecosystems, how they are affected by persuasive messages sent by digital platforms, how intensive advertising used by digital platforms affects user behavior, what is the level of stress or anxiety generated by social pressure related to UGC and UGB, or what are the limits of privacy in relation to understanding the behavior of online users based on the UGB study, among others.
Faced with this paradigm, for this Research Topic, we invite paper contributions related to any of the topics outlined below:
• Study of UGD and its influence on online user behavior;
• Study of user habits in digital environments in relation to UGD;
• Identification of new information sources related to online user behavior;
• Privacy concerns regarding the understanding of UGB and online user behavior;
• Identification of challenges for user’s behavior actions in digital environments;
• How companies can improve their understanding of online user behavior using UGD;
• New data-centric approaches to understand user behavior in digital environments;
• New data-driven models to analysis user behavior online using UGD;
• Identification of actions to modify user’s behavior online by analyzing UGD.
We welcome submission of the following article types: Original Research, Review, Community Case Study, Methods, Opinion, Systematic Review and Conceptual Analysis.
The global development of the Internet has led companies to modify their strategies in search of new ways to increase their profitability. Additionally, to this new digital environment, the increased use of social networks and the Internet in general have become habits for consumers to the point that there are millions of devices connected to the Internet that are constantly generating new data-points about users behaviors and their habits and actions online.
As the use of these technologies has become habitual for users, it has also become commonplace for users to share information about their experiences, opinions or interests publicly via social networks and known as user-generated data (UGD). The possible sources of such user data are the questions that are explicit asked to users to provide details or alternatively, these data can be also inferred from the study of user actions online.
Therefore, UGD can be categorized into user-generated content (UGC, i.e. information that users know they are creating publicly) and user-generated behavior (UGB, i.e. information that is generated as a result of user actions). In looking at these types of data sources, several studies have analyzed how to collect UGD, how to analyze or identify patterns, or how to extract insights that can help companies improve their strategies and communications in digital environments . However, there is a gap in scientific research about the study of challenges, opportunities and consequences for user’s behavior online, that the study of UGD -including both UGC and UGB- can bring to the understanding of how they perform their behave online.
Consequently, understanding the behavior of online users has become a key piece for the development of internet-focused strategies in which UGD have become a key concept to understand how users behave in digital ecosystems, how they are affected by persuasive messages sent by digital platforms, how intensive advertising used by digital platforms affects user behavior, what is the level of stress or anxiety generated by social pressure related to UGC and UGB, or what are the limits of privacy in relation to understanding the behavior of online users based on the UGB study, among others.
Faced with this paradigm, for this Research Topic, we invite paper contributions related to any of the topics outlined below:
• Study of UGD and its influence on online user behavior;
• Study of user habits in digital environments in relation to UGD;
• Identification of new information sources related to online user behavior;
• Privacy concerns regarding the understanding of UGB and online user behavior;
• Identification of challenges for user’s behavior actions in digital environments;
• How companies can improve their understanding of online user behavior using UGD;
• New data-centric approaches to understand user behavior in digital environments;
• New data-driven models to analysis user behavior online using UGD;
• Identification of actions to modify user’s behavior online by analyzing UGD.
We welcome submission of the following article types: Original Research, Review, Community Case Study, Methods, Opinion, Systematic Review and Conceptual Analysis.
