This work analyzes tweets linking to scientific papers to find out if the tweets are positive, or negative or do not express an opinion. This will inform the meaning of tweets as a measure of impact in the context of altmetrics. The following research questions are examined:
- In how far can sentiment analysis be used to detect positive or negative statements towards scientific papers expressed on Twitter?
- Do tweets linking to scientific papers express positive or negative opinions? How do sentiments differ by academic discipline?
- How do results affect the meaning of tweets to scientific papers as an altmetric indicator?
Inhaltsverzeichnis (Table of Contents)
- Introduction
- Materials and Methods
- Dataset
- Bibliographic information of tweeted documents
- Tweets
- Sentiment analysis
- The definition of a sentiment
- Sentiment analysis
- Methods
- Intellectual coding of sentiments
- Removing Twitter affordances
- Removing title terms
- Adapting the lexicon
- Removing non-English terms
- Calculating sentiments per discipline
- Dataset
- Results and Discussions
- The ground truth
- Sentiment analysis I
- Sentiment analysis II
- Sentiment analysis III
- Sentiment analysis IV
- Automated analysis of all tweets
- Results
- Discipline specific results
- The ground truth
- Conclusion
Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)
This work aims to analyze tweets linking to scientific papers to determine if they express positive, negative, or neutral opinions. This research seeks to understand the potential for sentiment analysis in uncovering opinions towards scientific papers on Twitter, particularly within the context of altmetrics. The work also explores how these sentiments differ across academic disciplines and how the findings impact the interpretation of tweets as indicators of scientific impact.
- Analyzing the sentiment expressed in tweets linking to scientific papers.
- Exploring the potential of sentiment analysis to detect positive or negative opinions about scientific papers on Twitter.
- Investigating how sentiments expressed in tweets vary across different academic disciplines.
- Evaluating the implications of sentiment analysis findings for interpreting tweets as indicators of scientific impact within the context of altmetrics.
Zusammenfassung der Kapitel (Chapter Summaries)
The introduction provides context for the study by discussing the importance of value freedom in scientific knowledge and the increasing significance of social media in scientific communication. It highlights the emerging field of altmetrics and its reliance on social media data, emphasizing the need to understand the sentiments expressed in tweets linking to scientific papers. The introduction outlines the research questions guiding the study.
The "Materials and Methods" section details the dataset used in the analysis, including the collection of bibliographic information of tweeted documents and the specific tweets themselves. The section also defines sentiment analysis and outlines the various methods employed, such as intellectual coding of sentiments, removing Twitter affordances, adapting the lexicon, and removing non-English terms. It explains how sentiments are calculated for each academic discipline.
Schlüsselwörter (Keywords)
This work explores the key concepts of sentiment analysis, altmetrics, scientific communication, Twitter, academic disciplines, and the impact of research. It investigates how sentiment analysis can be applied to understand opinions expressed about scientific papers on social media, particularly on Twitter, and its potential influence on the interpretation of altmetrics.
- Citar trabajo
- Natalie Friedrich (Autor), 2015, Applying sentiment analysis for tweets linking to scientific papers, Múnich, GRIN Verlag, https://www.grin.com/document/312043
