Mapping consumer sentiment toward wireless services using geospatial twitter data

Hyper-dense wireless network deployment is one of the popular solutions to meeting high capacity requirement for 5G delivery. However, current operator understanding of consumer satisfaction comes from call centers and base station quality-of-service (QoS) reports with poor geographic accuracy. The dramatic increase in geo-tagged social media posts adds a new potential to understand consumer satisfaction towards target-specific quality-of-experience (QoE) topics. In our paper, we focus on evaluating users’ opinion on wireless service-related topics by applying natural language processing (NLP) to geo-tagged Twitter data. Current generalized sentiment detection methods with generalized NLP corpora are not topic specific. Here, we develop a novel wireless service topic-specific sentiment framework, yielding higher targeting accuracy than generalized NLP frameworks. To do so, we first annotate a new sentiment corpus called SignalSentiWord (SSW) and compare its performance with two other popular corpus libraries, AFINN and SentiWordNet. We then apply three established machine learning methods, namely: Naïve Bayes (NB), Support Vector Machine (SVM), and Recurrent Neural Network (RNN) to build our topic-specific sentiment classifier. Furthermore, we discuss the capability of SSW to filter noisy and high-frequency irrelevant words to improve the performance of machine learning algorithms. Finally, the real-world testing results show that our proposed SSW improves the performance of NLP significantly

A study of cyber hate on Twitter with implications for social media governance strategies

This paper explores ways in which the harmful effects of cyber hate may be mitigated through mechanisms for enhancing the self-governance of new digital spaces. We report findings from a mixed methods study of responses to cyber hate posts, which aimed to: (i) understand how people interact in this context by undertaking qualitative interaction analysis and developing a statistical model to explain the volume of responses to cyber hate posted to Twitter, and (ii) explore use of machine learning techniques to assist in identifying cyber hate counter-speech

Designing assisted living technologies 'in the wild' : preliminary experiences with cultural probe methodology

Background There is growing interest in assisted living technologies to support independence at home. Such technologies should ideally be designed ‘in the wild’ i.e. taking account of how real people live in real homes and communities. The ATHENE (Assistive Technologies for Healthy Living in Elders: Needs Assessment by Ethnography) project seeks to illuminate the living needs of older people and facilitate the co-production with older people of technologies and services. This paper describes the development of a cultural probe tool produced as part of the ATHENE project and how it was used to support home visit interviews with elders with a range of ethnic and social backgrounds, family circumstances, health conditions and assisted living needs. Method Thirty one people aged 60 to 98 were visited in their homes on three occasions. Following an initial interview, participants were given a set of cultural probe materials, including a digital camera and the ‘Home and Life Scrapbook’ to complete in their own time for one week. Activities within the Home and Life Scrapbook included maps (indicating their relationships to people, places and objects), lists (e.g. likes, dislikes, things they were concerned about, things they were comfortable with), wishes (things they wanted to change or improve), body outline (indicating symptoms or impairments), home plan (room layouts of their homes to indicate spaces and objects used) and a diary. After one week, the researcher and participant reviewed any digital photos taken and the content of the Home and Life Scrapbook as part of the home visit interview. Findings The cultural probe facilitated collection of visual, narrative and material data by older people, and appeared to generate high levels of engagement from some participants. However, others used the probe minimally or not at all for various reasons including limited literacy, physical problems (e.g. holding a pen), lack of time or energy, limited emotional or psychological resources, life events, and acute illness. Discussions between researchers and participants about the materials collected (and sometimes about what had prevented them completing the tasks) helped elicit further information relevant to assisted living technology design. The probe materials were particularly helpful when having conversations with non-English speaking participants through an interpreter. Conclusions Cultural probe methods can help build a rich picture of the lives and experiences of older people to facilitate the co-production of assisted living technologies. But their application may be constrained by the participant’s physical, mental and emotional capacity. They are most effective when used as a tool to facilitate communication and development of a deeper understanding of older people’s needs

Mining and Visualizing Research Networks using the Artefact-Actor-Network Approach

Reinhardt, W., Wilke, A., Moi, M., Drachsler, H., & Sloep, P. B. (2012). Mining and Visualizing Research Networks using the Artefact-Actor-Network Approach. In A. Abraham (Ed.), Computational Social Networks. Mining and Visualization (pp. 233-268). Springer. Also available at http://www.springer.com/computer/communication+networks/book/978-1-4471-4053-5Virtual communities are increasingly relying on technologies and tools of the so-called Web 2.0. In the context of scientific events and topical Research Networks, researchers use Social Media as one main communication channel. This raises the question, how to monitor and analyze such Research Networks. In this chapter we argue that Artefact-Actor-Networks (AANs) serve well for modeling, storing and mining the social interactions around digital learning resources originating from various learning services. In order to deepen the model of AANs and its application to Research Networks, a relevant theoretical background as well as clues for a prototypical reference implementation are provided. This is followed by the analysis of six Research Networks and a detailed inspection of the results. Moreover, selected networks are visualized. Research Networks of the same type show similar descriptive measures while different types are not directly comparable to each other. Further, our analysis shows that narrowness of a Research Network's subject area can be predicted using the connectedness of semantic similarity networks. Finally conclusions are drawn and implications for future research are discussed

A new species of Raffaelea from beetle-infested Leucaena leucocephala

Species of Raffaelea (Ophiostomatales: Ascomycota) are obligate symbionts of ambrosia beetles, some of which pose a substantial threat to forest trees. Leucaena leucocephala is a small mimosoid tree species that is considered as an invasive weed in most of its introduced range globally. During a field expedition on the French island of Réunion, dying L. leucocephala trees were observed. Samples were taken from these trees and isolations made from symptomatic wood tissues that included beetle tunnels, but in the absence of the beetles themselves. Multiple isolates of a fungus resembling a Raffaelea species were obtained from the discoloured wood associated with the beetle tunnels. To determine their identity, microscopic examination was performed and DNA sequences for three gene regions (ITS, LSU, TUB) were obtained. Phylogenetic analyses based on these gene regions revealed that the isolates represent a new species of Raffaelea, described here as R. borbonica sp. nov. A pathogenicity test was conducted with the fungus, which was shown to cause lesions on the inoculated seedlings, but with a low level of aggressiveness.https://fuse-journal.orgpm2021BiochemistryForestry and Agricultural Biotechnology Institute (FABI)GeneticsMicrobiology and Plant Patholog

Wandering as a sociomaterial practice : extending the theorization of GPS tracking in cognitive impairment

Electronic tracking through global positioning systems (GPSs) is used to monitor people with cognitive impairment who “wander” outside the home. This ethnographic study explored how GPS-monitored wandering was experienced by individuals, lay carers, and professional staff. Seven in-depth case studies revealed that wandering was often an enjoyable and worthwhile activity and helped deal with uncertainty and threats to identity. In what were typically very complex care contexts, GPS devices were useful to the extent that they aligned with a wider sociomaterial care network that included lay carers, call centers, and health and social care professionals. In this context, “safe” wandering was a collaborative accomplishment that depended on the technology’s materiality, affordances, and aesthetic properties; a distributed knowledge of the individual and the places they wandered through, and a collective and dynamic interpretation of risk. Implications for design and delivery of GPS devices and services for cognitive impairment are discussed

Concentric and Eccentric Remodelling of the Left Ventricle and Its Association to Function in the Male Athletes Heart: An Exploratory Study

Aims To compare (1) conventional left ventricular (LV) functional parameters, (2) LV peak strain and strain rate and (3) LV temporal strain and strain rate curves in age, ethnicity and sport-matched athletes with concentric, eccentric and normal LV geometry.Methods Forty-five male athletes were categorised according to LV geometry including concentric remodelling/hypertrophy (CON), eccentric hypertrophy (ECC) or normal (NORM). Athletes were evaluated using conventional echocardiography and myocardial speck tracking, allowing the assessment of myocardial strain and strain rate; as well as twist mechanics. Results Concentric remodelling was associated with an increased ejection fraction (EF) compared to normal geometry athletes (64% (48-78%) and 56% (50-65%), respectively; p < 0.04). No differences in peak myocardial strain or strain rate were present between LV geometry groups including global longitudinal strain (GLS; CON -16.9% (-14.9-20.6%); ECC -17.9% (-13.0-22.1%); NORM -16.9% (-12.8-19.4%)), global circumferential strain (GCS; CON -18.1% (-13.5-24.5%); ECC -18.7% (-15.6-22.4%); NORM -18.0% (-13.5-19.7%)), global radial strain (GRS; CON 42.2% (30.3-70.5%); ECC 50.0% (39.2-60.0%); NORM 40.6 (29.9-57.0%)) and twist (CON 14.9° (3.7-25.3°); ECC 12.5° (6.3-20.8°); NORM 13.2° (8.8-24.2°)). Concentric and eccentric remodelling was associated with alterations in temporal myocardial strain and strain rate as compared to normal geometry athletes. Conclusion Physiological concentric and eccentric remodelling in the athletes heart is generally associated with normal LV function; with concentric remodelling associated with an increased EF. Physiological concentric and eccentric remodelling in the athletes heart has no effect on peak myocardial strain but superior deformation and untwisting is unmasked when assessing the temporal distribution