The Role of Trustworthiness Facets for Developing Social Media Applications: A Structured Literature Review

This work reviews existing research about attributes, which are assessed by individuals to evaluate the trustworthiness of (i) software applications, (ii) organizations (e.g., service providers), and (iii) other individuals. As these parties are part of social media services, previous research has identified the need for users to assess their trustworthiness. Based on the trustworthiness assessment, users decide whether they want to interact with them and whether such interactions appear safe. The literature review encompasses 264 works from which so-called trustworthiness facets of 100 papers could be identified. In addition to an overview of trustworthiness facets, this work further introduces a guideline for software engineers on how to select appropriate trustworthiness facets during the analysis of the problem space for the development of specific social media applications. It is exemplified by the problem of “catfishing” in online dating.

Study on Sentiment Classification Strategies Based on the Fuzzy Logic with Crow Search Algorithm

In recent times, sentiment analysis research has gained wide popularity. That situation is caused by the nature of online applications that allow users to express their opinions on events, services, or products through social media applications such as Twitter, Facebook, and Amazon. This paper proposes a novel sentiment classification method according to the Fuzzy rule-based system (FRBS) with crow search algorithm (CSA). FRBS is used to classify the polarity of sentences or documents, and the CSA is employed to optimize the best output from the fuzzy logic algorithm. The FRBS is applied to extract the sentiment and classify its polarity into negative, neutral, and positive. Sometimes, the outputs of the FRBS must be enhanced, especially since many variables are present and the rules between them overlap. For such cases, the CSA is used to solve this limitation faced by FRBS to optimize the outputs of FRBS and achieve the best result. We compared the performance of our proposed model with different machine learning algorithms, such as SVM, maximum entropy, boosting, and SWESA. We tested our model on three famous data sets collected from Amazon, Yelp, and IMDB. Experimental results demonstrated the effectiveness of the proposed model and achieved competitive performance in terms of accuracy, recall, precision, and the F–score.

Analisis Image Comments to Video Comments Ratio Instagram Pada 5 Tim Mobile Legend Bang Bang Terbaik di Indonesia Pada Tahun 2020

In this digital era, information and communication technology has made enormous progress, making it easier for people to interact through social media. One of the most widely used social media applications is Instagram. This study aims to find the ratios found on social media Instagram. These ratios can later be used to perform analyzes that can be measured mathematically. The research method used is exploratory to find the variables contained in Instagram. These variables will be juxtaposed to be tested for relevance so as to find the relevant ratio used to assess the performance of an Instagram account. The results of this Instagram social media research show that there are 14 ratios that can be used to assess, measure and compare the credibility of an Instagram account. The implication of the discovery of this ratio is that further researchers can conduct quantitative research in measuring, assessing and comparing accounts on Instagram.

How Queerness Goes Online

In this chapter, the author challenges the commonsense claim that the internet provides equally accessible resources that are free from stigma, prejudice, or discrimination. Through the stories of university students in their own words, this intersectional analysis explores how the internet certainly offers substantial benefits to queer and nonconforming youth; however, interpersonal bias and systems of oppression pervade online forms of communication and social media applications. Additionally, the author troubles the notion that the internet is experienced as a ‘safe space' for anonymous or uninhibited explorations of queer identity. In fact, despite the internet's practical affordances of identity work, there are severe limits to tolerance and inclusion in online sociality, and because of this, doing queer identity work online has the potential to exacerbate the isolating effects of homophobia and discrimination.

Predicting Catastrophic Events Using Machine Learning Models for Natural Language Processing

In recent years, there has been widespread improvement in communication technologies. Social media applications like Twitter have made it much easier for people to send and receive information. A direct application of this can be seen in the cases of disaster prediction and crisis. With people being able to share their observations, they can help spread the message of caution. However, the identification of warnings and analyzing the seriousness of text is not an easy task. Natural language processing (NLP) is one way that can be used to analyze various tweets for the same. Over the years, various NLP models have been developed that are capable of providing high accuracy when it comes to data prediction. In the chapter, the authors will analyze various NLP models like logistic regression, naive bayes, XGBoost, LSTM, and word embedding technologies like GloVe and transformer encoder like BERT for the purpose of predicting disaster warnings from the scrapped tweets. The authors focus on finding the best disaster prediction model that can help in warning people and the government.

Digital Communication in Museums and Museological Spaces

SMM (social media marketing) aims to produce content that users share in their various social media applications in order to increase brand exposure and broaden customer reach. There are numerous marketing techniques to apply in social media in order to involve the customer, some of which have costs and others that do not. Digitization was a real challenge for any museum, requiring cautious and well-planned action to be successful. In this sense, the nature of social networks demands the adoption of a constructivist perspective, that is, a perspective that involves affirmations of knowledge based on individual and collective experiences. Presently, being present in social networks presents itself as a high value advantage, allowing the exposure of the brand, product, or idea at a low cost to a large audience. This chapter aims to systematize some relational marketing best practices that are identified in the museums and museum spaces in “Baixo Alentejo” (Portugal). Specifically, some examples of relational marketing in terms of communication will be identified and analysed.

Interoperability in Internet of Media Things and Integration Big Media

Multimedia-related things is a new class of connected objects that can be searched, discovered, and composited on the internet of media things (IoMT). A huge amount of data sets come from audio-visual sources or have a multimedia nature. However, multimedia data is currently not incorporated in the big data (BD) frameworks. The research projects, standardization initiatives, and industrial activities for integration are outlined in this chapter. MPEG IoMT interoperability and network-based media processing (NBMP) framework as an instance of the big media (BM) reference model are explored. Conceptual model of IoT and big data integration for analytics is proposed. Big data analytics is rapidly evolving both in terms of functionality and the underlying model. The authors pointed out that IoMT analytics is closely related to big data analytics, which facilitates the integration of multimedia objects in big media applications in large-scale systems. These two technologies are mutually dependent and should be researched and developed jointly.

The Impact of Decentralized Technologies on Social Media Megacorporations

Social media is a mega-industry built by systematically monetizing the exploitation of human emotions, reactions, and biases. The authors explain how this industry became so profitable by creating a fear of missing out (FOMO) to command our attention, blending news and content in one feed to keep users 'in-app', and using powerful algorithms to promote more provocative posts, filter content, and trigger the reward centres of our brains. The authors examine how decentralized technologies, including cryptocurrencies, tokenization, and blockchain are being developed and deployed into new social media applications. The authors speculate on how these blockchain-backed startups could challenge the status quo and appeal to new expectations of user privacy, tighter regulation, and a more equitable monetization system.

Social Media in Business Decisions of MSMES

Social media has progressively grown in the last century and is now seen as a potential opportunity for various purposes, including the decision-making. Present work explores how social media platforms such as Facebook, Twitter, and Instagram etc. can be used to support the decision making process of MSMEs. The work is exploratory in nature and relevant literature has been reviewed to identify the decision making approaches at different managerial levels and how they have been integrated with the social media applications. Specific examples of Social media platforms have been discussed, considering the MSMEs’ business environment. Along with the practices, most important challenges to social media integration have also been presented.