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A novel framework for sentiment and emoticon-based clustering and indexing of tweets

Samuel, Avinash; Sharma, Dilip Kumar - In: Journal of information & knowledge management : JIKM 17 (2018) 2, pp. 1850013-1-18

Persistent link: https://www.econbiz.de/10011888357

URWF : user reputation based weightage framework for twitter micropost classification

Bukhari, Asad; Qamar, Usman; Ghazia, Ume - In: Information systems and e-business management : ISeB 15 (2017) 3, pp. 623-659

Persistent link: https://www.econbiz.de/10011758824

Sochi 2014 Olympics on Twitter : perspectives of hosts and guests

Kirilenko, Andrei; Stepchenkova, Svetlana - In: Tourism management : research, policies, practice 63 (2017), pp. 54-65

Persistent link: https://www.econbiz.de/10011746330

Brand analysis in social network services : results from content analysis in twitter regarding the US smartphone market

Hajikhani, Arash; Porras, Jari; Melkas, Helinä - In: International journal of innovation and technology … 14 (2017) 2, pp. 1740008-1-21

Persistent link: https://www.econbiz.de/10011640007

Computing consumer sentiment in Germany via social media data

Karaman Örsal, Deniz Dilan; Sturm, Silke - 2021 - Preliminary draft

Survey-based consumer confidence indicators are mostly reported with adelay and are a result of time consuming and expensive consumer surveys.In this study, to measure the current consumer confidence in Germany, wedevelop an approach, in which we compute the consumer sentiment...

Persistent link: https://www.econbiz.de/10012423780

A year of pandemic : levels, changes and validity of well-being data from Twitter : evidence from ten countries

Sarracino, Francesco; Greyling, Talita; O'Connor, Kelsey J. - 2021

National Happiness (GNH), a country-level index built applying sentiment analysis to data from Twitter. Our aim is to describe … assess the validity of data sourced from Twitter, we exploit various sources of survey data, such as Eurobarometer and …

Persistent link: https://www.econbiz.de/10012506627