Untitled

doi:10.1002/asi.v57:3

Cited by 224 publications

(13 citation statements)

References 348 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Lexical style markers (words per message and words per sentence) were used in Cambria et al (2011) to analyse web blogs. Previous studies have shown style markers to be highly common in web discourse (Abbasi, 2005;Zheng et al, 2006).…”

Section: Explicit Featuresmentioning

confidence: 98%

Overview and Future Opportunities of Sentiment Analysis Approaches for Big Data

Sharef¹,

Zin²,

Nadali³

2016

Journal of Computer Science

View full text Add to dashboard Cite

Abstract:The ability to exploit public sentiment in social media is increasingly considered as an important tool for market understanding, customer segmentation and stock price prediction for strategic marketing planning and manoeuvring. This evolution of technology adoption is energised by the healthy growth in big data framework, which caused applications based on Sentiment Analysis (SA) in big data to become common for businesses. However, scarce works have studied the gaps of SA application in big data. The contribution of this paper is two-fold: (i) this study reviews the state of the art of SA approaches. including sentiment polarity detection, SA features (explicit and implicit), sentiment classification techniques and applications of SA and (ii) this study reviews the suitability of SA approaches for application in the big data frameworks, as well as highlights the gaps and suggests future works that should be explored. SA studies are predicted to be expanded into approaches that utilise scalability, possess high adaptability for source variation, velocity and veracity to maximise value mining for the benefit of the users.

show abstract

Section: Explicit Featuresmentioning

confidence: 98%

Overview and Future Opportunities of Sentiment Analysis Approaches for Big Data

Sharef¹,

Zin²,

Nadali³

2016

Journal of Computer Science

View full text Add to dashboard Cite

show abstract

“…It was developed by Professor Chen Chaomei of the Drexel University Department of Computer and Information Science. CiteSpace can measure and analyse documents in specific fields and reflect the objective situation of scientific development [23][24][25]. Bibliometrix is an R-tool that enables data processing, analysis and visualization [26].…”

Section: Application Softwarementioning

confidence: 99%

The status of and trends in the pharmacology of berberine: a bibliometric review [1985–2018]

et al. 2020

View full text Add to dashboard Cite

Berberine has significant antibacterial and antipyretic effects and is a commonly used drug for treating infectious diarrhoea. The current research data show that the pharmacological effects of berberine are numerous and complex, and researchers have been enthusiastic about this field. To allow researchers to quickly understand the field and to provide references for the direction of research, using bibliometrics, we analysed 1426 articles, dating from 1985 to 2018, in the field of berberine pharmacology. The research articles we found came from 69 countries/regions, 1381 institutions, 5675 authors, and 325 journals; they contained 3794 key words; they were written in 7 languages; and they were of 2 article types. This study summarizes and discusses the evolution of the historical themes of berberine pharmacology as well as the status quo and the future development directions from a holistic perspective.

show abstract

“…Most of the work in IR with multisources is classified as federated search [Avrahami et al 2006;Aditya and Jaya 2008;Callan 2000] also known as distributed information retrieval. In federated search, instead of having one central collection indexed by one search engine, there are many distributed text collections each indexed by a search engine .…”

Section: Federated Searchmentioning

confidence: 99%

“…The FedLemur project [Avrahami et al 2006] is an illustrate example of federal search engine that is built on top of statistical data issued from 100 US federal agencies. Instead of building a centralized collection, which can quickly get outdated, authors show that it is better to build local search engines in many distributed nodes (one per agency).…”

Section: Federated Searchmentioning

confidence: 99%

Aggregated search

2014

View full text Add to dashboard Cite

Traditional search engines return ranked lists of search results. It is up to the user to scroll this list, scan within different documents, and assemble information that fulfill his/her information need. Aggregated search represents a new class of approaches where the information is not only retrieved but also assembled. This is the current evolution in Web search, where diverse content (images, videos, etc.) and relational content (similar entities, features) are included in search results. In this survey, we propose a simple analysis framework for aggregated search and an overview of existing work. We start with related work in related domains such as federated search, natural language generation, and question answering. Then we focus on more recent trends, namely cross vertical aggregated search and relational aggregated search, which are already present in current Web search.

show abstract

Untitled

Cited by 224 publications

References 348 publications

Overview and Future Opportunities of Sentiment Analysis Approaches for Big Data

Overview and Future Opportunities of Sentiment Analysis Approaches for Big Data

The status of and trends in the pharmacology of berberine: a bibliometric review [1985–2018]

Aggregated search

Contact Info

Product

Resources

About