Recent Developments and Implications in Web Analysis

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Applications".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 4160

Special Issue Editor


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Guest Editor
Bictevac Laboratory—Business Information and Communication Technologies in Value Chains Laboratory, Department of Agribusiness and Supply Chain Management, School of Applied Economics and Social Sciences, Agricultural University of Athens, 118 55 Athens, Greece
Interests: digital marketing; social media; big data; web analytics; strategy; simulation; negotiations; mathematics

Special Issue Information

Dear Colleagues,

The MDPI journal Information invites submissions to a Special Issue on “Recent Developments and Implications in Web Analysis”.

Recent developments in web analysis have witnessed a significant evolution in both technological advancements and analytical approaches. Advanced machine learning algorithms, natural language processing, and sentiment analysis techniques have been increasingly employed to extract meaningful insights from the vast amount of data generated on the web. Integrating deep learning models has enhanced the ability to detect subtle patterns, sentiments, and trends, providing a more nuanced understanding of user behavior. Additionally, there is a growing emphasis on real-time analysis, enabling quicker responses to emerging events and discussions, and even blockchain applications.

The referred developments and implications in web analysis have profound connections with various information scopes, reflecting the broader impact on society, business, and research. In the realm of business and marketing, web analysis provides valuable insights into consumer behavior, preferences, and trends. This information scope allows companies to tailor their strategies, enhance customer engagement, and optimize marketing campaigns for better reach and impact.

In the context of public opinion and discourse, web analysis becomes a crucial tool for understanding sentiment, identifying key issues, and gauging public sentiment. This information scope is particularly relevant for policymakers, analysts, and government agencies, enabling them to make informed decisions and respond effectively to public concerns.

From a societal perspective, web analysis contributes to the information scope of crisis management and emergency response. Real-time monitoring of web platforms helps identify emerging crises, enabling faster and more effective responses from authorities. This is particularly important in situations where timely information can make a significant difference in mitigating the impact of crises.

However, as web analysis becomes more sophisticated, ethical considerations within the information scope have gained prominence. Issues related to privacy, data security, and algorithmic bias need careful attention to ensure the responsible and fair use of information extracted from web platforms. Balancing the benefits of web analysis with ethical considerations is crucial for maintaining public trust and safeguarding individual rights.

In summary, recent developments in web analysis impact a wide range of information scopes, including business, politics, crisis management, and societal dynamics. Understanding and navigating the implications within these scopes are essential for leveraging the benefits of web analysis while addressing ethical concerns and ensuring the responsible use of data.

Prof. Dr. Damianos P. Sakas
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • web analytics
  • utility of web platforms
  • role of the web
  • blockchain implications
  • big data
  • recent developments in web analysis
  • implications of web analysis
  • artificial intelligence (AI)
  • machine learning (ML)
  • web user behavior
  • digital marketing
  • brand engagement
  • web crisis management
  • ethical concerns
  • privacy and data security

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Published Papers (2 papers)

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Research

16 pages, 672 KiB  
Article
AI-Enhanced Personality Identification of Websites
by Shafquat Ali Chishti, Iman Ardekani and Soheil Varastehpour
Information 2024, 15(10), 623; https://doi.org/10.3390/info15100623 - 10 Oct 2024
Viewed by 473
Abstract
This paper addresses the challenge of objectively determining a website’s personality by developing a methodology based on automated quantitative analysis, thus avoiding the biases inherent in human surveys. Utilizing a database of 3000 websites, data extraction tools gather relevant data, which are then [...] Read more.
This paper addresses the challenge of objectively determining a website’s personality by developing a methodology based on automated quantitative analysis, thus avoiding the biases inherent in human surveys. Utilizing a database of 3000 websites, data extraction tools gather relevant data, which are then analyzed using Artificial Intelligence (AI) techniques, including machine learning (ML) and natural language processing. Four ML algorithms—K-means, Expectation Maximization, Hierarchical Agglomerative Clustering, and DBSCAN—are implemented to assess and classify website personality traits. Each algorithm’s strengths and weaknesses are evaluated in terms of data organization, cluster flexibility, and handling of outliers. A software tool is developed to facilitate the research process, from database creation and data extraction to ML application and results analysis. Experimental validation, conducted with identical training and testing datasets, achieves a success rate of up to 94% (with an Error of 50%) in accurately identifying website personality, which is validated by subsequent surveys. The research highlights significant relationships between website attributes and personality traits, offering practical applications for website developers. For instance, developers can use these insights to design websites that align with business goals, enhance customer engagement, and foster brand loyalty. Additionally, the methodology can be applied to creating culturally resonant websites, thus supporting New Zealand’s cultural initiatives and promoting cross-cultural understanding. This research lays the groundwork for future studies and has broad applicability across various domains, demonstrating the potential for automated, unbiased website personality classification. Full article
(This article belongs to the Special Issue Recent Developments and Implications in Web Analysis)
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20 pages, 2000 KiB  
Article
Social Networks and Digital Influencers in the Online Purchasing Decision Process
by Maria José Angélico Gonçalves, Adriana Oliveira, António Abreu and Anabela Mesquita
Information 2024, 15(10), 601; https://doi.org/10.3390/info15100601 - 30 Sep 2024
Viewed by 3414
Abstract
Social networks have become a significant part of people’s daily lives, particularly in the purchasing process. In this context, digital influencers have played an essential role in shaping consumers’ opinions. In this sense, studying the role of social networks and influencers in the [...] Read more.
Social networks have become a significant part of people’s daily lives, particularly in the purchasing process. In this context, digital influencers have played an essential role in shaping consumers’ opinions. In this sense, studying the role of social networks and influencers in the online product purchase decision process was considered pertinent. We selected two technology adoption models to fulfill this purpose: the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). We conducted an exploratory study using a quantitative approach, with data being collected through a questionnaire distributed online. The statistical analysis of the empirical model employed a partial least squares structural equation modeling (PLS-SEM) technique. Analyzing the 135 responses allowed us to conclude that social networks are relevant in consumers’ purchase decision process. This research highlights the importance of the credibility of influencers, emotional connections with audiences, and the dynamics of the media in shaping consumer behavior. It highlights the strong influence of digital influencers on purchasing decisions and makes a methodological contribution with a rigorous empirical model. This study also suggests avenues for future research in order to deepen the understanding of influencer and social media marketing strategies. Full article
(This article belongs to the Special Issue Recent Developments and Implications in Web Analysis)
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