scholarly journals Problem Presentation of Echo Phenomenon on Social Listening and Proposal of Avoidance Method for It

2017 ◽  
Vol 112 ◽  
pp. 1412-1419 ◽  
Author(s):  
Daisuke Sakamoto ◽  
Ryo Uchida ◽  
Kazuhiko Tsuda
Keyword(s):  
Problem Presentation ◽  
Social Listening

Social Listening to Create Bespoke Customer Experiences: Best Practices for Hospitality Operators

2021 ◽  
pp. 193896552199308
Author(s):  
Kathryn A. LaTour ◽  
Ana Brant
Keyword(s):  
Social Media ◽  
Best Practices ◽  
Real Time ◽  
Brand Image ◽  
Customer Experience ◽  
Current Experience ◽  
Social Listening

Most hospitality operators use social media in their communications as a means to communicate brand image and provide information to customers. Our focus is on a two-way exchange whereby a customer’s social posting is reacted to in real-time by the provider to enhance the customer’s current experience. Using social media in this way is new, and the provider needs to carefully balance privacy and personalization. We describe the process by which the Dorchester Collection Customer Experience (CX) Team approached its social listening program and share lessons to identify best practices for hospitality operators wanting to delight their customers through insights gained from social listening.

scholarly journals Social listening – revealing Parkinson’s disease over day and night

BMC Neurology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hui Zhang ◽  
Fanwen Meng ◽  
Xingyu Li ◽  
Yali Ning ◽  
Meng Cai
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Unmet Needs ◽  
Unmet Need ◽  
Motor Symptoms ◽  
Motor Complications ◽  
Sentiment Score ◽  
Negative Sentiment ◽  
Non Motor Symptoms ◽  
Social Listening

Abstract Background Nocturnal symptoms in Parkinson’s disease are often treated after management of daytime manifestations. In order to better understand the unmet needs of nocturnal symptoms management, we analyzed the characteristics and burden of nocturnal symptoms from patients’ perspectives and explored their changes over time. Overall symptoms (occurring at day or night) were collected to compare whether the unmet needs related to nocturnal symptoms and to overall symptoms are different. Methods We used a Social Listening big-data technique to analyze large amounts of Parkinson’s disease symptoms in dialogues available from social media platforms in 2016 to 2018. These symptoms were classified as either overall symptoms or nocturnal symptoms. We used share of voice (SOV) of symptoms as a proportion of total dialogues per year to reflect the characteristics of symptoms. Negative sentiment score of symptoms was analyzed to find out their related burden. Results We found the SOV for overall motor symptoms was 79% and had not increased between 2016 and 2018 (79%, p = 0.5). The SOV for non-motor symptoms was 69% and had grown by 7% in 2018 (p <  0.01). The SOV for motor complications was 9% and had increased by 6% in 2018 (p <  0.01). The SOV of motor symptoms was larger than non-motor symptoms and motor complications (p <  0.01). The SOV of non-motor symptoms was larger than motor complications (p <  0.01). For nocturnal symptoms, 45% of the analyzed PD population reported nocturnal symptoms in 2018, growing by 6% (p <  0.01). The SOV for nocturnal-occurring motor symptoms was higher than most non-motor symptoms. However, non-motor symptoms had the higher increases and evoked higher negative sentiment regardless of whether they occurred during the day or night. For symptoms that can occur at either day or night, each nocturnal symptom was rated with a higher negative sentiment score than the same symptom during the day. Conclusions The growing SOV and the greater negative sentiment of nocturnal symptoms suggest management of nocturnal symptoms is an unmet need of patients. A greater emphasis on detecting and treating nocturnal symptoms with 24-h care is encouraged.

Effect of Criterional Learning-Set Training Where Problem Objects are Encased in Plexiglas Bins

1965 ◽  
Vol 21 (2) ◽  
pp. 544-546 ◽  
Author(s):  
Joseph W. Ternes ◽  
Enrique J. Abordo ◽  
Duane M. Rumbaugh
Keyword(s):  
Squirrel Monkey ◽  
Problem Presentation ◽  
Learning Set

Extended criterional learning-set (LS) training prior to test on a series of 6-tr/LS problems provided a significant, but transitory, advantage for Ss trained in a situation where problem objects were encased in Plexiglas bins. Criterional training appeared to compensate, at least partially, for those characteristics of this method of problem presentation which render squirrel monkey Ss learning-setless when given just 6-tr/LS training (Rumbaugh, Ternes, & Abordo, 1965).

The Insights Industry: Towards a Performativity Turn in Market Research

2021 ◽  
pp. 147078532110391
Author(s):  
Carlos A. Diaz Ruiz
Keyword(s):  
Market Research ◽  
Data Science ◽  
Competitive Intelligence ◽  
Research Techniques ◽  
Social Listening

While market research has been the cornerstone of the intelligence ecosystem, the emergence of ‘insights’ vendors is re-shaping the market. Adjacent practices, ranging from competitive intelligence, social listening and data science, could relegate market research to legacy status in firms. This investigation explores how expert market researchers respond to the commoditisation of market research techniques and their diminishing access to the client’s organisation to address this issue. The findings show that market researchers are adapting – effectively reinventing themselves as ‘insights’ professionals – through the following four initiatives: (1) offering solution services, (2) creating architectures that integrate organic and designed data, (3) making heroes in the client’s organisation and (4) forging performative relationships based on strategic guidance. These initiatives shift market research from ostensive (descriptive or declarative) to performative (effectual or actionable). Theoretically, the article conceptualises the changes in the market research industry through the performativity lens.

scholarly journals EARS – A WHO Platform for AI-Supported Real-Time Online Social Listening of COVID-19 Conversations

2021 ◽  
Author(s):  
Tina D. Purnat ◽  
Harry Wilson ◽  
Tim Nguyen ◽  
Sylvie Briand
Keyword(s):  
Social Media ◽  
Real Time ◽  
Public Spaces ◽  
Data Sources ◽  
Effective Response ◽  
Real Time Information ◽  
Time Information ◽  
Social Listening

As the COVID-19 pandemic evolves, the accompanying infodemic is being amplified through social media and has challenged effective response. The WHO Early AI-supported Response with Social Listening (EARS) is a platform that summarizes real-time information about how people are talking about COVID-19 in public spaces online in 20 pilot countries and in four languages. The aim of the platform is to better integrate social listening with other data sources and analyses that can inform infodemic response.

Sign in / Sign up

Export Citation Format

Share Document