This work investigates empirically the impact of political party control over its candidates or vice versa on winning an election using a Natural Language Processing (NLP) technique called Sentiment Analysis (SA). To do this, a set of 7430 tweets bearing or related to #AnambraDecides2017 was streamed during the November 18, 2017 Anambra State gubernatorial election. These are Twitter discussions on the top 5 political parties and their candidates termed political actors in this paper. We conduct polarity and subjectivity sentiment analyses on all the tweets considering time as a useful dimension of SA. Furthermore, we use the word frequency to find words most associated to the political actors in a given time. We find most talked about topics using a topic modeling algorithm and how the computed sentiments and most frequent words are related to the topics per political actor. Among other things, we deduced from the experimental results that even though a political party serves as a platform that sales the personality of a candidate, the acceptance of the candidate/party adds to the winning of an election. For example, we found the winner of the election Willie Obiano benefiting from the values his party share among the people of the State. Associating his name with his party All Progressive Grand Alliance (APGA) displays more positive sentiments and the Subjective Sentiment Analysis indicates that Twitter users mentioning APGA are less emotionally subjective in their tweets than the other parties.
Recently, researchers have identified several challenges attendant to the teaching and learning of Geography in Nigerian secondary schools. Consequently, in order to address these issues we propose GeoNaija-an educational mobile application platform that aid the teaching and learning of Geography. For the development of the application, we employed the cyclical ever-evolving analysis, design, development, implementation, and evaluation (ADDIE) instructional design method. This method was chosen due to the fact that it is popular, easy to apply, allows for rapid prototyping, saves times and provides continual feedback. The newly developed mobile app will make the teaching and learning of Geography concepts easier, captivating and delightful for both the students and the teachers. The significance and value of the research was made clearly evident through a survey that elicited students' responses on questions relating to the app's presentation, visual, navigation and accessibility design. 90 secondary students was used for the survey. The study affirmed that developed mobile application will positively change the perspectives of the students and help eliminate the gap between the conventional and other informal forms of education.
Abstract-Sensor networks are appealing targets for malicious attacks that invade the network with the aim of depleting the confidentiality, availability and integrity (CIA) features/parameters of neighboring sensor nodes. This is due to its open communication, minimal resources and its deployment in un-trusted, unguarded and unfriendly terrains. To restrict illegitimate users or malicious attackers (such as worms) network analysts have suggested network access control (NAC). Specifically, we apply NAC to wireless sensor network epidemic models in order to investigate distribution density, transmission range and sensor area/field. Our analyses involved analytical expressions of two sensor fields gleaned from literature. Additionally, we explored the possibilities of infectivity of sensor nodes at the exposed class using the two expressions for sensor field topologies. We also derived the reproduction ratios and solutions at several equilibrium points for the models. It is our hope that that our work herein would impact sensor deployment decisions for organizations that utilize wireless sensor networks for meaningful daily activities.
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