Sentiment Analysis

Lamba, Manika; Madhusudhan, Margam

doi:10.1007/978-3-030-85085-2_7

Cited by 6 publications

(4 citation statements)

References 16 publications

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“…Sentiment analysis was conducted using the MPQA Subjectivity Lexicon (Khoo & Johnkhan, 2018; Weibe et al, 2005). Lamba and Madhusudhan (2022) defined sentiment analysis as a natural language processing approach that recognizes significant patterns of information and features from a large collection of text. The sentiment analysis “analyzes thought, attitude, views, opinions, beliefs, comments, requests, questions, and preferences expressed by an author based on emotion rather than a reason in the form of text towards entities like services, issues, individuals, products, events, topics, organizations, and their attributes” (Lamba & Madhusudhan, 2022, p. 191).…”

Section: Discussionmentioning

confidence: 99%

Working Across Boundaries: School Leaders Redefining Communities of Practice Through Twitter

Bailey,

Kaiser,

Rhone

et al. 2023

NASSP Bulletin

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Attrition rates among school leaders have risen in recent years, and scholars cite a lack of meaningful connections and responsive professional learning as leading reasons why they are leaving the field. School leaders are called to navigate unfamiliar and complex challenges, often working in isolation with limited opportunities for collaboration and professional growth. Social media forums, like Twitter, have potential to support a Community of Practice to facilitate learning around school leadership; however, there is a lack of scholarship exploring how school leaders use social media to support their needs. This mixed-methods study used sentiment and content analysis along with a phronetic iterative approach to explore how school leaders use Twitter to connect with others in the field. The umbrella categories of efficacy, agency, and resiliency emerged from the analysis, offering a glimpse into potential connections made through social media. The findings of this exploratory study suggest that principals are seeking connection, encouragement, and professional learning, yet further development in this area could help inform more formal practices to fill the gap in access to informal professional learning.

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Section: Discussionmentioning

confidence: 99%

Working Across Boundaries: School Leaders Redefining Communities of Practice Through Twitter

Bailey,

Kaiser,

Rhone

et al. 2023

NASSP Bulletin

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show abstract

“…Sentiment analysis is a natural language processing (NLP) technique that identifies important patterns of information and features from a large text. Therefore, it is considered an important option for processing qualitative data, When you can analyze thoughts, attitudes, views, opinions, beliefs, comments, requests, questions, and preferences expressed by a consumer based on emotion rather than a reason in text form toward entities such as services, problems, individuals, products, events, topics, organizations, and their attributes [2], It is a powerful technique in Artificial intelligence that has important business applications.…”

Section: Literature Review Sentimental Analysismentioning

confidence: 99%

“…Extract tweets based on conditions for categorizing [1] "Inicia tu negocio online desde la comodidad de la casa, un coworking o café y ¡Conviértete en tu propia jefa! 👩💻\n\nEl Negocio de la Asistencia Virtual para Emprendedoras \n\n¡Te invitamos a registrarte con 50% de descuento!\n\nAprenda Fácil Online ✅\nhttps://t.co/9rJTfALiTx https://t.co/RroBvX7ydb" [2] "Estoy harta de fingir que no quiero poner un negocio y ser parte de las ✨emprendedoras✨"…”

Section: Tableunclassified

Sentimental analysis of female entrepreneurs based on public tweets

Barrios

Hernández²,

Duana-Avila³

2023

jas

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After the declaration of the COVID 19 pandemic, jobs and occupations had to return to normal, however many people lost their main source of resources, so the incorporation of women in different ventures has been a flag to get ahead with work for their families, so the objective of this work is to identify opinions about entrepreneurs, using the technique of sentimental analysis to classify unstructured information from public tweets using for data processing, the Rstudio software with the retweet, word cloud and emo libraries collecting the feelings that people have through the microblogging platform Twitter in the period from June 20 to July 10, 2022. The results show that 74.53% of users perceive positive and very positive feelings toward women entrepreneurs, so it can be concluded that the impact of the incorporation of women entrepreneurs, which although at this time is still uncertain is perceived as an important factor for the economic recovery.

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“…It analyses the thoughts, attitudes, viewpoints, opinions, convictions, remarks, requests, inquiries, and interests expressed by the author based on feelings not reason in the form of texts, with entities such as service, issue, person, product, event, object, organizations, and their attributes. It identifies the author’s overall attitudes toward a text, which could be anything from blog posts to product reviews to online forums to speeches to data from databases to social media documents [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

A BERT Framework to Sentiment Analysis of Tweets

Bello

Leung

2023

Sensors

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Sentiment analysis has been widely used in microblogging sites such as Twitter in recent decades, where millions of users express their opinions and thoughts because of its short and simple manner of expression. Several studies reveal the state of sentiment which does not express sentiment based on the user context because of different lengths and ambiguous emotional information. Hence, this study proposes text classification with the use of bidirectional encoder representations from transformers (BERT) for natural language processing with other variants. The experimental findings demonstrate that the combination of BERT with CNN, BERT with RNN, and BERT with BiLSTM performs well in terms of accuracy rate, precision rate, recall rate, and F1-score compared to when it was used with Word2vec and when it was used with no variant.

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Sentiment Analysis

Cited by 6 publications

References 16 publications

Working Across Boundaries: School Leaders Redefining Communities of Practice Through Twitter

Working Across Boundaries: School Leaders Redefining Communities of Practice Through Twitter

Sentimental analysis of female entrepreneurs based on public tweets

A BERT Framework to Sentiment Analysis of Tweets

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