On Semantic Word Cloud Representation

We study the problem of computing semantic-preserving word clouds in which semantically related words are close to each other. While several heuristic approaches have been described in the literature, we formalize the underlying geometric algorithm problem: Word Rectangle Adjacency Contact (WRAC). In this model each word is associated with rectangle with fixed dimensions, and the goal is to represent semantically related words by ensuring that the two corresponding rectangles touch. We design and analyze efficient polynomial-time algorithms for some variants of the WRAC problem, show that several general variants are NP-hard, and describe a number of approximation algorithms. Finally, we experimentally demonstrate that our theoretically-sound algorithms outperform the early heuristics

Word-forest Visualization of Discussed Topics in Social Media Comments

It becomes a norm for many organizations to use social network as a platform for internal and external communication means. Due to its extensive usage, most large organizations recognize the importance of capturing disseminated information across the social networks for the benefit of their internal perusal. However, managing and keeping track of all the information which are hidden in the piles of comments are hard to deal with. This paper presents a system that can extract, analyze and visualize information from the comments. As for the case study, Facebook is chosen due to its ability to allow people to comment freely and repetitively. The comments were extracted from selected post in Facebook using its API. The relationship between the words inside the comments will then be determined by using relationship table. Then, a visualization technique, word-forest, is used to visualize the relation between the prepared table. The prototype is tested by using selected posts in specific Facebook accounts. The result shows that users can quickly get overviews on the topics that have been discussed without having to go through all the comments on the Facebook. The system has great potential to be further explored as one of the means to get internal and external workers or public perception unobtrusively at real-time and real-life setting

Overlap Removal of Dimensionality Reduction Scatterplot Layouts

Dimensionality Reduction (DR) scatterplot layouts have become a ubiquitous visualization tool for analyzing multidimensional data items with presence in different areas. Despite its popularity, scatterplots suffer from occlusion, especially when markers convey information, making it troublesome for users to estimate items' groups' sizes and, more importantly, potentially obfuscating critical items for the analysis under execution. Different strategies have been devised to address this issue, either producing overlap-free layouts, lacking the powerful capabilities of contemporary DR techniques in uncover interesting data patterns, or eliminating overlaps as a post-processing strategy. Despite the good results of post-processing techniques, the best methods typically expand or distort the scatterplot area, thus reducing markers' size (sometimes) to unreadable dimensions, defeating the purpose of removing overlaps. This paper presents a novel post-processing strategy to remove DR layouts' overlaps that faithfully preserves the original layout's characteristics and markers' sizes. We show that the proposed strategy surpasses the state-of-the-art in overlap removal through an extensive comparative evaluation considering multiple different metrics while it is 2 or 3 orders of magnitude faster for large datasets.Comment: 11 pages and 9 figure

UTAUT Model, Smart Exhibition Sorted by Relevance: Word Cloud Visualization Review

The aim of the paper is to introduce a visualization method with word cloud visualization to illustrate evolution of the smart exhibition, other relevant exhibition modes with virtual presentation and the articles in the application of UTAUT model in a set of documents. The relationship between UTAUT model and smart area, and the smart exhibition and some other smart areas is to be presented rapidly and evidently. This article provides interactive visual analysis of smart exhibition sorted by relevance and the industries or fields in the application of the UTAUT Model by a set of key words, at different time points based on the presentation of D2 or D3 to highlight the core word to make the trend of the smart exhibition clearly understood

Comparative Study: Penggunaan Media Sosial oleh Pemerintah Kota Bandung dan Kota Gold Coast

Penelitian ini bertujuan untuk meliahat bagaimana pemerintah pada kota yang menerapkan konsep smart city memanfaatkan platform media sosisal. Kasus yang diambil adalah akun twitter Majelis Kota Gold Coast dan Pemerintah Kota Bandung. Penelitian ini merupakan penelitian deskriptif kualitatif dengan memanfaatkan software NVivo 12 Plus sebagai alat analisis. Data yang digunakan berasal dari akun twitter resmi @cityofgoldcoast milik Majelis Kota Gold Coast dan akun @humasbdg milik Pemerintah Kota Bandung. Hasil dari penelitian ini adalah kedua akun tersebut memiliki kesamaan dalam hal penyampaian informasi dan pola interaksi. Kedua akun dalam menyampaikan informasi tidak secara lengkap, melainkan mencantumkan tautan yang terhubung ke website resmi pemerintah. Selanjutnya kedua akun melakukan pola interaksi yang hanya satu arah. Perbedaan kedua akun terletak pada topik pembahasan disetiap akun dan persebaran informasi. Akun @cityofgoldcoast cenderung mentweet terkait kondisi aktual yang terjadi. Berbeda dengan akun @humasbdg yang memiliki topik pembahasan seputar keprotokoleran. Selain itu kedua akun memiliki persebaran informasi yang menyesuaikan dengan interaksi yg dilakukan. Diakhir penulis memberikan catatan terkait penelitian lanjutan dari pada penelitian ini

Visual Decision-Making in Real-Time Business Intelligence: A Social Media Marketing Example

This paper presents a study into the use of visualizations in real-time business intelligence. Different visualization designs for a social media marketing use case are tested and evaluated through the lens of cognitive load theory. By reducing the complexity of visualizations and subsequently cognitive load, end-users can achieve markedly improved decision-making performance in situations where time is critical and data is fast-paced