Using social media data to understand mobile customer experience and behavior

Understanding mobile customer experience and behavior is an important task for cellular service providers to improve the satisfaction of their customers. To that end, cellular service providers regularly measure the properties of their mobile network, such as signal strength, dropped calls, call blockage, and radio interface failures (RIFs). In addition to these passive measurements collected within the network, understanding customer sentiment from direct customer feedback is also an important means of evaluating user experience. Customers have varied perceptions of mobile network quality, and also react differently to advertising, news articles, and the introduction of new equipment and services. Traditional methods used to assess customer sentiment include direct surveys and mining the transcripts of calls made to customer care centers. Along with this feedback provided directly to the service providers, the rise in social media potentially presents new opportunities to gain further insight into customers by mining public social media data as well. According to a note from one of the largest online social network (OSN) sites in the US [7], as of September 2010 there are 175 million registered users, and 95 million text messages communicated among users per day. Additionally, many OSNs provide APIs to retrieve publically available message data, which can be used to collect this data for analysis and interpretation. Our plan is to correlate different sources of measurements and user feedback to understand the social media usage patterns from mobile data users in a large nationwide cellular network. In particular, we are interested in quantifying the traffic volume, the growing trend of social media usage and how it interacts with traditional communication channels, such as voice calls, text messaging, etc. In addition, we are interested in detecting interesting network events from users' communication on OSN sites and studying the temporal aspects - how the various types of user feedback behave with respect to timing. We develop a novel approach which combines burst detection and text mining to detect emerging issues from online messages on a large OSN network. Through a case study, our method shows promising results in identifying a burst of activities using the OSN feedback, whereas customer care notes exhibit noticeable delays in detecting such an event which may lead to unnecessary operational expenses. --Mobile customer experience,social media,text data mining,customer feedback

Traveling Waves and Shocks in a Viscoelastic Generalization of Burgers\u27 Equation

We consider traveling wave phenomena for a viscoelastic generalization of Burgers\u27 equation. For asymptotically constant velocity profiles we find three classes of solutions corresponding to smooth traveling waves, piecewise smooth waves, and piecewise constant (shock) solutions. Each solution type is possible for a given pair of asymptotic limits, and we characterize the dynamics in terms of the relaxation time and viscosity

Enset‐based agricultural systems in Ethiopia: A systematic review of production trends, agronomy, processing and the wider food security applications of a neglected banana relative

Enset (Ensete ventricosum (Welw.) Cheesman) is the major starch staple of the Ethiopian Highlands, where its unique attributes enhance the food security of approximately 20 million people and have earned it the title “The Tree Against Hunger”. Yet enset‐based agriculture is virtually unknown outside of its narrow zone of cultivation, despite growing wild across much of East and Southern Africa. Here, we review historical production data to show that the area of land under enset production in Ethiopia has reportedly increased 46% in two decades, whilst yield increased 12‐fold over the same period, making enset the second most produced crop species in Ethiopia—though we critically evaluate potential issues with these data. Furthermore, we address a major challenge in the development and wider cultivation of enset, by reviewing and synthesizing the complex and fragmented agronomic and ethnobotanic knowledge associated with this species; including farming systems, processing methods, products, medicinal uses and cultural importance. Finally, we provide a framework to improve the quality, consistency and comparability of data collected across culturally diverse enset‐based agricultural systems to enhanced sustainable use of this neglected starch staple. In conclusion, we discuss the challenges and opportunities for enset cultivation beyond its restricted distribution, and the regional food security potential it could afford smallholders elsewhere in Southern and East Africa

Bacterial diseases of bananas and enset: Current state of knowledge and integrated approaches toward sustainable management

Bacterial diseases of bananas and enset have not received, until recently, an equal amount of attention compared to other major threats to banana production such as the fungal diseases black leaf streak (Mycosphaerella fijiensis) and Fusarium wilt (Fusarium oxysporum f. sp. cubense). However, bacteria cause significant impacts on bananas globally and management practices are not always well known or adopted by farmers. Bacterial diseases in bananas and enset can be divided into three groups: (1) Ralstonia-associated diseases (Moko/Bugtok disease caused by Ralstonia solanacearum and banana blood disease caused by R. syzygii subsp. celebesensis); (2) Xanthomonas wilt of banana and enset, caused by Xanthomonas campestris pv. musacearum and (3) Erwinia-associated diseases (bacterial head rot or tip-over disease Erwinia carotovora ssp. carotovora and E. chrysanthemi), bacterial rhizome and pseudostem wet rot (Dickeya paradisiaca formerly E. chrysanthemi pv. paradisiaca). Other bacterial diseases of less widespread importance include: bacterial wilt of abaca, Javanese vascular wilt and bacterial fingertip rot (probably caused by Ralstonia spp., unconfirmed). This review describes global distribution, symptoms, pathogenic diversity, epidemiology and the state of the art for sustainable disease management of the major bacterial wilts currently affecting banana and enset. (Résumé d'auteur

High-speed PAM4-based Optical SDM Interconnects with Directly Modulated Long-wavelength VCSEL

This paper reports the demonstration of high-speed PAM-4 transmission using a 1.5-{\mu}m single-mode vertical cavity surface emitting laser (SM-VCSEL) over multicore fiber with 7 cores over different distances. We have successfully generated up to 70 Gbaud 4-level pulse amplitude modulation (PAM-4) signals with a VCSEL in optical back-to-back, and transmitted 50 Gbaud PAM-4 signals over both 1-km dispersion-uncompensated and 10-km dispersion-compensated in each core, enabling a total data throughput of 700 Gbps over the 7-core fiber. Moreover, 56 Gbaud PAM-4 over 1-km has also been shown, whereby unfortunately not all cores provide the required 3.8 $\times$ 10 $^{-3}$ bit error rate (BER) for the 7% overhead-hard decision forward error correction (7% OH HDFEC). The limited bandwidth of the VCSEL and the adverse chromatic dispersion of the fiber are suppressed with pre-equalization based on accurate end-to-end channel characterizations. With a digital post-equalization, BER performance below the 7% OH-HDFEC limit is achieved over all cores. The demonstrated results show a great potential to realize high-capacity and compact short-reach optical interconnects for data centers.Comment: 7 pages, accepted to publication in 'Journal of Lightwave Technology (JLT

Experimental Demonstration of 503.61-Gbit/s DMT over 10-km 7-Core Fiber with 1.5-\mu m SM-VCSEL for Optical Interconnects

We experimentally demonstrate a net-rate 503.61-Gbit/s discrete multitone (DMT) transmission over 10-km 7-core fiber with 1.5-\mu m single mode VCSEL, where low-complexity kernelrecursive-least-squares algorithm is employed for nonlinear channel equalization.Comment: 3 pages, 44th European Conference on Optical Communication (ECOC 2018), Rome, Italy, 201