Economic Development through Business Profiling: A Text Analysis Based Approach

Author(s):  
Rohit Parimi ◽  
Doina Caragea ◽  
Dale Wunderlich
2021 ◽  
Vol 10 (1) ◽  
pp. 11
Author(s):  
Dramane Thiombiano ◽  
Ahmet Yiğitalp TULGA

This paper investigates the perceptions of Africans on Chinese infrastructure development in Nigeria and Ethiopia. Using a sentiment-based text analysis methodology, this paper attempts to understand the perceptions and sentiments of Nigerians and Ethiopians on Chinese infrastructure projects. For this purpose, we choose Nigeria and Ethiopia as important destinations of Chinese investment in Africa. Africa is not only rich in natural resources; it also possesses a young population that makes the bulk of the working force. Despite its rapid GDP growth and growing urbanization, the continent is still entangled in the midst of underdevelopment, poverty and an acute lack of infrastructure to stimulate and sustain this economic development. China’s investment in the continent is trying to tackle this infrastructure bottleneck by investing in the building of infrastructures such as roads, railways, ports and highways. The results show some overall positive popular sentiments towards Chinese infrastructure projects from both countries. To conclude, we argue for a need of more scrutiny from the parts of the leadership in Africa given the potential issues related to Chinese infrastructure projects in Africa.


Crisis ◽  
2016 ◽  
Vol 37 (2) ◽  
pp. 140-147 ◽  
Author(s):  
Michael J. Egnoto ◽  
Darrin J. Griffin

Abstract. Background: Identifying precursors that will aid in the discovery of individuals who may harm themselves or others has long been a focus of scholarly research. Aim: This work set out to determine if it is possible to use the legacy tokens of active shooters and notes left from individuals who completed suicide to uncover signals that foreshadow their behavior. Method: A total of 25 suicide notes and 21 legacy tokens were compared with a sample of over 20,000 student writings for a preliminary computer-assisted text analysis to determine what differences can be coded with existing computer software to better identify students who may commit self-harm or harm to others. Results: The results support that text analysis techniques with the Linguistic Inquiry and Word Count (LIWC) tool are effective for identifying suicidal or homicidal writings as distinct from each other and from a variety of student writings in an automated fashion. Conclusion: Findings indicate support for automated identification of writings that were associated with harm to self, harm to others, and various other student writing products. This work begins to uncover the viability or larger scale, low cost methods of automatic detection for individuals suffering from harmful ideation.


Author(s):  
Natalie Shapira ◽  
Gal Lazarus ◽  
Yoav Goldberg ◽  
Eva Gilboa-Schechtman ◽  
Rivka Tuval-Mashiach ◽  
...  

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