The Efficiency of Social Network Services Management in Organizations. An In-Depth Analysis Applying Machine Learning Algorithms and Multiple Linear Regressions

Matosas-López, Luis; Romero-Ania, Alberto

doi:10.3390/app10155167

Cited by 11 publications

(6 citation statements)

References 52 publications

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“…Once the multiple linear regression analysis was completed, the authors corroborated the validity of the regression model obtained. For this purpose, in accordance with Matosas-López and Romero-Ania [54], the regression residuals were analyzed using, on the one hand, the Shapiro-Wilk test, and on the other, the Durbin-Watson test.…”

Section: Discussionmentioning

confidence: 99%

How to Improve Customer Engagement in Social Networks: A Study of Spanish Brands in the Automotive Industry

Matosas-López

Romero-Ania

2021

JTAER

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The objective of this research is to identify to what extent volumes, components, time slots, and publication topics improve customer engagement with Spanish automotive brands through social networks. The study considers thirteen brands and the total number of publications created by them in 2020 (23,670 publications) on the social network Twitter. Applying machine learning algorithms followed by multiple linear regression techniques, the authors examine how the variables previously mentioned affect a customer engagement indicator developed for this purpose. The results reveal that while publication components (links, mentions, and hashtags) and the publication time slot do not affect customer engagement, the volume of retweets made by the brand and publications on customer experience topics (without a direct commercial purpose) significantly improve the customer engagement indicator. The authors conclude that customer engagement in social networks can only be improved by conducting exhaustive analyses of activity data for these platforms. However, such analyses must not be done via generic multisector analyses, which only generate superficial and inapplicable knowledge, but rather through detailed studies for each sector.

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Section: Discussionmentioning

confidence: 99%

How to Improve Customer Engagement in Social Networks: A Study of Spanish Brands in the Automotive Industry

Matosas-López

Romero-Ania

2021

JTAER

Self Cite

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“…e reflected and refracted illumination enters the camera, reaches the sensor through the lens, and finally forms the digital image that we see through a series of operations such as exposure, sampling, and denoising. From formulas (7) and ( 8), it can be seen that the image forming process can be simplified as the convolution of the original analog signal and the bidirectional reflection distribution function.…”

Section: Generation Methods Of Subpixel Samples Based On Gaussian Low-pass Filteringmentioning

confidence: 99%

“…Machine learning algorithm is an algorithm that automatically learns useful information from data. A formal definition of “learning” is given from the point of view of computer program [ 7 ]: if P is the performance measure criterion of task T , and if a computer program can improve the performance criterion P of task T by using experience E , it is said that for task T and performance measure P the program has learned from experience E .…”

Section: Machine Learningmentioning

confidence: 99%

Application of Digital Image Based on Machine Learning in Media Art Design

2021

Computational Intelligence and Neuroscience

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In digital media art, expressive force is an important art form of media. This paper studies digital images that have the same effect when applied to media art. The research object is media art images, and the application effect of the proposed algorithm is related to the media art images. The development of digital image technology has brought revolutionary changes to traditional media art expression techniques. In this paper, a partial-pixel interpolation technique based on convolutional neural network is proposed. Supervised training of convolutional neural networks requires predetermining the input and target output of the network, namely, integer image and fractional image in this paper. To solve the problem that the subpixel sample cannot be obtained, this paper first analyzes the imaging principle of digital image and proposes a subpixel sample generation algorithm based on Gaussian low-pass filter and polyphase sampling. From the perspective of rate distortion optimization, the purpose of pixel motion compensation is to improve the accuracy of interframe prediction. Therefore, this paper defines pixel motion compensation as an interframe regression problem, that is, the mapping process of the reference image integral pixel sample to the current image sample to be encoded. In this paper, a generalized partial-pixel interpolation model is proposed for bidirectional prediction. The partial-pixel interpolation of bidirectional prediction is regarded as a binary regression model; that is, the integral pixel reference block in two directions is mapped to the current block to be coded. It further studies how to apply the trained digital images to media art design more flexibly and efficiently.

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“…Microblogging can be used to assess brands according to brands' personality dimensions [11,4]. In a different approach [12] the authors identify which variables enable organizations to manage their social network services more efficiently. Besides microblogging platforms, Facebook and Instagram are social networks that often cover the brands' and public perception topics.…”

Section: Related Workmentioning

confidence: 99%

Integrated Visual Analysis for Brand Perception on Different Social Networks

Scherer¹,

Sanvido²,

Silveira³

et al. 2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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Nowadays, social media fosters billions of users and has become an important communication source. Social media empowered the users' opinions supplying quick and less costly feedback compared to traditional survey methods. However, analyzing a brand through its social media is not trivial and raises challenges. To benefit from its data, brands need easy-to-use tools to help them understand the data gathered. Thus, the main goal of this work is to provide a visual analysis approach composed of several interactive visualization techniques to support brands to obtain insights from their social media. Besides the analyses allowed by integrating different social media data, the proposed approach has a well-defined pipeline that can be extended and used without programming knowledge. We conducted two case studies to explore these analyses, one for Netflix and one for Amazon Prime Video data. The results help us to highlight the approach's potential and possible future investigations. * 'The results of this work were achieved in cooperation with HP Brasil Indústria e Comércio de Equipamentos Eletrônicos LTDA. and Hewlett Packard Brasil LTDA. using incentives of Brazilian Informatics Law (Law nº 8.2.48 of 1991), and was partially supported by UolEdTech. Manssour thanks the financial support of the CNPq Scholarship-Brazil (308456/2020-3). The authors also would like to thank the financial support of the PDTI Program, financed by Dell Computers of Brazil Ltd. (Law 8.248/91).'

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The Efficiency of Social Network Services Management in Organizations. An In-Depth Analysis Applying Machine Learning Algorithms and Multiple Linear Regressions

Cited by 11 publications

References 52 publications

How to Improve Customer Engagement in Social Networks: A Study of Spanish Brands in the Automotive Industry

How to Improve Customer Engagement in Social Networks: A Study of Spanish Brands in the Automotive Industry

Application of Digital Image Based on Machine Learning in Media Art Design

Integrated Visual Analysis for Brand Perception on Different Social Networks

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