Analisis Hubs and Authorities Centrality menggunakan Probabilistic Affinity Index (PAI) pada graf berarah-berbobot dalam Social Network Analysis

Social media merupakan wadah dalam melakukan interaksi yang terhubung ke jaringan internet, Twitter adalah salah satu contoh dari social media. Dalam twitter terkadang seseorang tidak ingin tertinggal in- formasi terkait topik tertentu, sehingga perlu mem-follow user yang berkaitan dengan topik tersebut agar informasi dapat diperoleh dengan cepat. Pada penelitian ini dilakukan analisis yang menerapkan metode Hubs and Authorities Centrality untuk menentukan perangkingan user dan metode Probabilistic Affinity In- dex untuk pembobotan nilai. Hasil perangkingan authority centrality dapat dijadikan daftar rekomendasi suatu user yang berperan atau mempunyai informasi mengenai topik tertentu dan hasil perangkingan hub centrality dapat dijadikan daftar rekomendasi suatu user yang memiliki ketertarikan pada topik tertentu. Dari pengujian pada penelitian ini, perubahan jumlah user lain yang berelasi dengan user mempunyai rata- rata terbesar perubahan nilai centrality sebesar 0.01188. Sementara perubahan jumlah relasi mempunyai rata-rata terbesar perubahan nilai centrality sebesar 1.44087x10?9. Berdasarkan pengujian tersebut, jum- lah user lain yang berelasi dengan user mempunyai pengaruh besar pada hasil perangkingan dibandingkan dengan jumlah relasi yang dimiliki oleh user

Grammars for generating isiXhosa and isiZulu weather bulletin verbs

The Met Office has investigated the use of natural language generation (NLG) technologies to streamline the production of weather forecasts. Their approach would be of great benefit in South Africa because there is no fast and large scale producer, automated or otherwise, of textual weather summaries for Nguni languages. This is because of, among other things, the complexity of Nguni languages. The structure of these languages is very different from Indo-European languages, and therefore we cannot reuse existing technologies that were developed for the latter group. Traditional NLG techniques such as templates are not compatible with 'Bantu' languages, and existing works that document scaled-down 'Bantu' language grammars are also not sufficient to generate weather text. In pursuance of generating weather text in isiXhosa and isiZulu - we restricted our text to only verbs in order to ensure a manageable scope. In particular, we have developed a corpus of weather sentences in order to determine verb features. We then created context free verbal grammar rules using an incremental approach. The quality of these rules was evaluated using two linguists. We then investigated the grammatical similarity of isiZulu verbs with their isiXhosa counterparts, and the extent to which a singular merged set of grammar rules can be used to produce correct verbs for both languages. The similarity analysis of the two languages was done through the developed rules' parse trees, and by applying binary similarity measures on the sets of verbs generated by the rules. The parse trees show that the differences between the verb's components are minor, and the similarity measures indicate that the verb sets are at most 59.5% similar (Driver-Kroeber metric). We also examined the importance of the phonological conditioning process by developing functions that calculate the ratio of verbs that will require conditioning out of the total strings that can be generated. We have found that the phonological conditioning process affects at least 45% of strings for isiXhosa, and at least 67% of strings for isiZulu depending on the type of verb root that is used. Overall, this work shows that the differences between isiXhosa and isiZulu verbs are minor, however, the exploitation of these similarities for the goal of creating a unified rule set for both languages cannot be achieved without significant maintainability compromises because there are dependencies that exist in one language and not the other between the verb's 'modules'. Furthermore, the phonological conditioning process should be implemented in order to improve generated text due to the high ratio of verbs it affects