media mining
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Technovation ◽  
2022 ◽  
pp. 102447
Author(s):  
Jose Ramon Saura ◽  
Daniel Palacios-Marqués ◽  
Domingo Ribeiro-Soriano

2021 ◽  
Author(s):  
Tharun P

The approach I described is straightforward, related to COVID-19 SARS based tweets and the symptoms, that people tweet about. Also, social media mining for health application reports was shared in many different tasks of 2021. The motto at the back of this observe is to analyses tweets of COVID-19 based symptoms. By performing BERT model and text classification with XLNET with which uses to classify text and purpose of the texts (i.e.) tweets. So that I can get a deep understanding of the texts. When developing the system, I used two models the XLNet and DistilBERT for the text sorting task, but the outcome was XLNET out-performs the given approach to the best accuracy achieved. Now I discover a whole lot vital for as it should be categorizing tweets as encompassing self-said COVID-19 indications. Whether or not a tweets associated with COVID-19 is a non-public report or an information point out to the virus. Which gives test accuracy to an F1 score of 96%.


2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Wahiba Ben Abdessalem Karaa ◽  
Eman Alkhammash ◽  
Thabet Slimani ◽  
Myriam Hadjouni

The paper presents a recommendation model for developing new smart city and smart health projects. The objective is to provide recommendations to citizens about smart city and smart health startups to improve entrepreneurship and leadership. These recommendations may lead to the country’s advancement and the improvement of national income and reduce unemployment. This work focuses on designing and implementing an approach for processing and analyzing tweets inclosing data related to smart city and smart health startups and providing recommended projects as well as their required skills and competencies. This approach is based on tweets mining through a machine learning method, the Word2Vec algorithm, combined with a recommendation technique conducted via an ontology-based method. This approach allows discovering the relevant startup projects in the context of smart cities and makes links to the needed skills and competencies of users. A system was implemented to validate this approach. The attained performance metrics related to precision, recall, and F-measure are, respectively, 95%, 66%, and 79%, showing that the results are very encouraging.


Author(s):  
Jennifer Pierre ◽  
Morgan Currie ◽  
Britt Paris ◽  
Irene Pasquetto

This paper examines the potential role of social media in enhancing the understanding and perception of victims of police killings and the data collection surrounding these incidents. Through a series of content analysis and social media mining exercises, the authors observe the emergence of three distinct types of social media content offered on victims of police killings: persistence of the deceased’s activity across social media, sensational commentary on videos and blog postings, and memorials on Facebook, Twitter, and Tumblr. As part of a larger investigation of the availability and accessibility of official police homicide data, this paper aims to present social media data as a potentially powerful source of information to supplement quantitative reports. This process may be especially useful for the most affected communities, particularly BIPOC communities.


Author(s):  
Jonathan Koss ◽  
Astrid Rheinlaender ◽  
Hubert Truebel ◽  
Sabine Bohnet-Joschko

Technovation ◽  
2021 ◽  
Vol 107 ◽  
pp. 102322
Author(s):  
Sercan Ozcan ◽  
Metin Suloglu ◽  
C. Okan Sakar ◽  
Sushant Chatufale

2021 ◽  
Vol 21 (2) ◽  
pp. 12
Author(s):  
Karine De Almeida Paula ◽  
Teresa Cristina De Almeida Faria

O trabalho objetiva analisar a percepção dos turistas acerca dos principais marcos históricos religiosos da cidade de Tiradentes – MG, com o intuito de identificar a imagem perceptiva formada pelos mesmos a partir dos dados contidos na plataforma TripAdvisor. Em se tratando dos procedimentos metodológicos, foram analisados os dados obtidos junto ao TripAdvisor no período compreendido entre janeiro de 2012 a julho de 2020. Para obtenção e análise dos dados recorreu-se à técnica conhecida como Web Scraping (WS), utilizada em tarefas que envolvam mineração na web. A partir das técnicas empregadas, desenvolveuse nuvens de palavras, com representação de frequência de textos. Com base nas análises foi possível observar diferentes formas de percepção para os diferentes marcos religiosos da cidade, sendo que, em alguns momentos, a arquitetura presente nas edificações não apresentou expressividade singular, sendo substituída por elementos temporais, históricos e externalidades vizinhas.


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