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  • 30 Jul 2021 11:22 AM | Kathy Doering (Administrator)

    by Ashley Cooksley , Elizabeth Koenig ,

    July, 29,2021 - Mediapost.com 

    It may be hard to believe it’s a thing, but World Emoji Day was “celebrated” (is that the right word for it?) on July 17. Still, for anyone over the age of 40 or so, the fact that this rudimentary, sometimes confounding, symbol language -- started in Japan in 1999 -- has its own day is enough to trigger a flurry of eye-roll emojis.

    But emojis are serious business in 2021, and marketers need to be aware of what these seemingly innocent images hiding inside our phone’s keyboard actually mean -- and how context fits into that understanding.

    That was never more apparent than recently in the U.K. when, following England’s football team losing the EURO championship, a wave of disgusting racist epithets were posted on the social media accounts of three Black English players: Bukayo Saka, Jadon Sancho and Marcus Rashford.

    Accompanying the awful hate speech were repeated uses of the monkey and banana emojis. The abuse was so bad that the term “Saka’s Instagram” began trending on Twitter as commentary escalated about people being so openly racist.

    There have been calls to ban the monkey emoji for years. The bottom line is, emoji meanings vary, and marketers and brands’ social media managers need to exercise caution with them.

    Emojis are not just happy or sad faces or fruits and vegetables. Today, they contribute to conversations in different ways. Symbolically, they communicate identity by drawing from old symbolism -- like the rose emoji, which is tied to antiauthoritarian labor movements going back to the 18th century. More notoriously, we all now know that that frog emoji known as “Pepe” represents a lot more than just a frog since being adopted by the alt right in the U.S.

    Moreover, emojis today can signal particular subcultures, like the ape emoji (a reference to a meme taken from the movie “Rise of the Planet of the Apes”) signifying WallStreetBets, a subculture of investors that played a role in the recent overvaluing of stocks for companies like GameStop. Similarly, a baseball cap emoji is a new iteration of a community-specific term in hip hop that means “lie” or “BS.”

    Language is always changing to adapt to cultural shifts. Merriam Webster adds many new words to the dictionary every year. Since emojis are also a language, meanings change over time and new emoji are added to reflect changes in culture as well.

    For example, the popular “crying/laughing” emoji has been replaced by Gen-Zers with a skull emoji or “I’m dead” as a substitute. The two fingers touching emoji is used to show feeling shy, or timid. And the brain emoji -- well, let’s just say it has nothing to do with intelligence (on platforms like TikTok, this emoji represents "giving head.")

    Brands need to be aware of these shifts in emoji use to better understand what is being said about their brand and products. Moreover, if brands are looking to create a credible voice online, they need to understand the context surrounding emojis. After all, it’s possible that baseball cap emoji may just be referring to your favorite American pastime.


  • 29 Jun 2021 3:27 PM | Kathy Doering (Administrator)

    Great when we are able to use social media insights to better understand patient experiences. 


    AJMC.com Managed Markets Network

    An analysis of social media posts provides insight into patient experiences of acute lymphoblastic leukemia (ALL) and the therapies that treat it.

    Analyzing patient-reported information shared on social media by patients with acute lymphoblastic leukemia (ALL) allowed researchers to gain insight into patient experiences on novel therapies that improve treatment of the disease but cause substantial treatment-related impacts on health-related quality of life (HRQOL).

    The results were presented at the European Hematology Association 2021 Virtual Congress.

    “Patient-reported information (PRI) shared on social media provides a distinct opportunity to understand patients’ perspectives outside the formal research context,” the authors explained.

    They collected data from YouTube and 3 patient advocacy websites—Patient Power, The Patient Story, and Leukaemia Care—as well as reviewed video footage and discussion blogs. They extracted data from social media posts, including demographic information and accompanying disease information.

    The investigators assessed 935 social media posts, but ultimately included just 63 posts (40 videos, 5 comments, and 18 blog posts) from 41 unique contributors in the final review. Prior to ALL treatment, the symptoms the individuals most frequently discussed were fatigue (48.8%), shortness of breath (31.7%), and bruising (29.3%).

    They also reported the following HRQOL impacts of ALL and its treatment:

    Physical limitations (19.5%), including mobility, fine motor functioning, and lifting/carrying

    Daily life (26.8%), including self-care, daily tasks, and leisure activities/hobbies

    Work (39.0%), including the ability to keep employment, change in career path, and financial impact

    Social functioning (4.9%), including changes to existing relationships and the ability to look after children

    Psychological/emotional impact (61.0%), including shock, feat of the future, depression, anxiety, self-image, anger/frustration, and loneliness

    Treatment of adverse effects, such as neutropenia, change in taste, and nausea, were associated with changes in patients’ eating habits and weight loss.

    The majority (75.6%) of patients had self-reported being treated with chemotherapy, followed by bone marrow transplant (26.8%), radiation therapy (12.2%), chimeric antigen receptor T-cell therapy (12.2%), stem cell transplant (12.2%), immunotherapy (9.8%), steroid treatment (9.8%), blood transfusion (2.4%), and umbilical cord blood transplant (2.4%).

    Overall, approximately half (48.8%) reported experience with multiple treatment types. These treatments were associated with long-lasting adverse effects such as fatigue (26.8%), hair loss (27.8%), and nausea (22.0%).

    “ALL symptoms primarily affected patients’ physical functioning, activities of daily living, and ability to work, while treatment-related symptoms and impacts primarily affected patients’ emotional well-being,” the researchers noted.

    Reference

    Morrison R, Sikirica S, Crawford R, et al. The patient experience of acute lymphoblastic leukemia and its treatment: a social media review. Presented at: EHA2021 Virtual; June 9-17, 2021. Poster EP370.


  • 26 Apr 2021 11:34 AM | Kathy Doering (Administrator)

    Posted on April 26, 2021 by eChatter

    www.e-chatter.net

    By: Amanda Brown

    social media

    Apps on the Rise

    Since COVID-19 we have seen an immeasurable social media shift with so many people across the globe staying home. This has drastically impacted ecommerce and their shopping in general. Due to these changes, spending and investing in apps has significantly increased.

    According to AppAnnie,“Global spend on apps surged by 40% in a year, with $32 billion spent on in-app purchases across iOS and Google Play globally in Q1 2021. It’s the biggest quarter since records began – and the figure is 40% up on the same quarter for 2020.”

    This trend will continue, adapting to consumer behaviors within the market. So, what does this mean for you as an investigator? You are going to want to stay up to date on apps that are beginning to trend and the shift in consumer behavior will be a good cross reference for this.

    So, what are some apps that are taking off you ask? Let’s unpack the significance of a few of them.

    Clubhouse & It’s New Rival, Live Audio Rooms

    While TikTok still reigns supreme in top downloadable apps, Clubhouse is taking the world by storm with over 6 million active users to date. At first, this unique platform was being used by developers in Silicon Valley, then inevitably hit mainstream. Clubhouse is an audio-based concept with no video or text present. Someone can host a chat in a room with a few individuals to thousands of people. The catch? You must be invited by someone to join in all the Clubhouse fun. Currently, you can sign up on a wait list for Clubhouse access. Exclusivity is playing a big part in all the hype over this app. So much so that Mark Zuckerberg has decided to compete.

    Live Audio Rooms is launching this summer and Mark Zuckerberg’s company announced products that will have an emphasis on voice content over images, video, and texts. This will start off with only a few individuals allowed in, another example of exclusivity, and then will release to everyone a few months after. Eventually this summer we should see this open to the public and through Messenger.

    The Competition Gets Even More Real

    If you thought Mark Zuckerberg was just feeling competitive by adding Live Audio Rooms, think again. He is not only taking on this endeavor but a few other apps that have the same audio-chat feature. Creating audio suites is what he believes is the future of virtual networking

    “We think that audio is […] going to be a first-class medium and there are all these difference products to be built across the whole spectrum,” Zuckerberg in an audio interview with tech journalist Casey Newton on Discord.

    What’s Coming

    Soundbites:

    A social audio app that’s entire emphasis is on adding tone to a quote, poem, or joke that you have posted. Writing something out is not enough when it comes to communicating online. Soundbites was created because you can miss sarcasm and inflection just by writing something. Being able to add your tone and voice allows the reader to understand you fully.

    Facebook Podcasts:

    According to Facebook’s post, more than 170 million Facebook users already follow and interact with podcast pages and groups on the platform. Therefore, there is no denying an investment into a more streamline podcast interaction is in Facebook’s future. They are working on allowing podcasts to be streamed directly from their platform. Allowing users to not only listen to their favorite podcast more easily, but to also like, engage, and comment with podcast creators.

    Hotline:

    Although considered another competitor to Clubhouse this app is slightly different. Also, slightly different than Live Audio Rooms. Hotline is aimed at “knowledge experts”, according to a Facebook spokeswoman. Experts in their field such as healthcare, or finance. Users will be able to engage and chat with these specialists. Hosting an event through Hotline can be recorded and currently there is not an audience size limit. More development is in progress with this app. As to how hosts would make money off this has yet to be determined.

    Audio Creation:

    Facebook is even more inventive with new concepts like voice morphing technologies, noise cancellation features, and speech-to-text concepts that will allow users to build upon their creativity when posting text. According to laptopmag.com, if you are on a busy street corner recording yourself, a noise cancellation feature will allow you to come across clearly to your audience and cancel that background noise for you.

    Sound Collection:

    This is a collection of sound effects and song clips that a user can scroll through that will take their content to the next level. Allowing users to layer their content with new features is the goal of this new concept.

    Is There an End in Sight?

    Unfortunately, the answer to this is no, but the good news is we are here to stay up on all these changes for you. With our research background, it is in our nature to constantly be on the lookout for what is up and coming. To test out and find new OSINT skills to tackle these new technology advances. Sign up for your Newsletter for all the exclusive details.



  • 18 Feb 2021 9:32 AM | Kathy Doering (Administrator)

    Published in Quirk's Magazine Jan.Feb/2021

    Rodolphe Barrere, Co-Founder and CEO, Potloc 

    With 3.96 billion people using social media today, sampling on social channels is the next research frontier


    According to Hootsuite’s latest Digital Statshot Report, more than half of the world’s population is now on social media. Not ever in human history have we had such vast access to information, people, news and interconnectivity. The implications of this are numerous in terms of human communication, how people interact with brands and businesses worldwide and how companies extract consumers’ insights. 

    When I started building Potloc in 2014, I recognized the power social media had to gather people’s thoughts about what was going on in their immediate vicinity. We helped local businesses identify what offering, location and combination of customer experiences would appeal to their trade area. It didn’t take us long to realize we were sitting on a real gold mine of insights. The samples we were getting through social channels were on point, with relevant respondents answering our surveys with no other incentive than their desire to be part of the conversation. Through testing and trying different approaches, we soon discovered that we could leverage the targeting capabilities social platforms offer to reach any person with a social account, anywhere in the world. This realization allowed us to scale our operation and offer our services anywhere you could find someone “thumbing-up” through their social feed. This approach might seem obvious but the reality is that sampling in social media as a methodology has been largely overlooked as a great way to reach niche audiences and fresh respondents on a global scale.

    The medium is the message

    The key to nailing social sampling boils down to really understanding the medium. Social channels’ dynamics are quite different from those of very controlled environments like focus groups, online panels or even face-to-face interviews. To gain insights from social users, you need to understand how the social ecosystem works: people use social media mostly when they have downtime – moments of free time they dedicate to browsing their feeds, a golden opportunity to interact with them. On average, the world’s internet users spend two hours and 24 minutes using social networks across all devices each day, accounting for more than one-third of our total internet time. “Intercepting” them during this time increases their chances of taking a survey and focusing on expressing their opinions. Non-intrusive research and how companies approach potential respondents also plays an essential role in conducting successful sampling. The messaging not only needs to be appealing to them but also relevant and at the right time. After more than seven years of developing our expertise in social media sampling and the technology that enables it, we know how to increase the relevancy factor. Here are my thoughts:

    Location, location, location

    Social media is the perfect place to reach respondents, no matter the incidence rate or the quotas you have set. The beauty of targeting people via social networks is that you can reach them at a broad location level (country, state, zip code), down to a half-mile radius. Through geotargeting or more conventional location-based targeting, businesses can reach highly relevant audiences. People who live, work, study or just transit through the targeted area are real-life respondents that have a treasure trove of insights to share, from in-store CX to people’s experience attending an event or having seen a particular billboard at a specific location. The possibilities are endless.

    The right targeting can get you niche audiences with low incidence rates

    Again, the nature of social networks is that people are there to share. Think about it – when you browse through your feed on any of these networks, you are already interacting with brands and businesses to a certain degree. This gives researchers unprecedented opportunities to access the largest consumer group globally and extract insights directly from them. The essential advantage here is the ability to target a specific population, not only by geographical area, as I mentioned before, but also by age, gender, interests, language, profession, income, etc. We’ve worked for the largest consulting firms globally, like Bain & Company, BCG and EY, to help them reach very niche and specific audiences for their clients, where panels tend to struggle. Hitting the bull’s-eye with targeting on social guarantees a more representative, diverse and genuine sample of the broader population, with fresh respondents that reflect real people living in the real world.

    The biases to keep in mind

    Just like any other methodology, we deal with some biases that come with social sampling. We have identified four of these as well as ways to tackle them:

    1. Coverage bias: For targeting consumers on social networks, they need to meet certain conditions. They must have access to the internet, have a social media account and be active users. This might show an under-representation of men and older people. However, older generations like Baby Boomers and the Silent Generation have adopted social platforms in great numbers. In the U.S. alone, 72% of Americans between the ages of 50 and 64 are on Facebook and 62% of “online seniors” aged above 65 are also there.
    2. Ad platforms’ algorithm bias: Taking Facebook as an example, its advertising algorithm is set up to minimize cost-per-click. This means it pushes survey ads primarily to the least-expensive audiences (under-representing the population). Setting up quotas to balance the sample becomes essential to counter this bias, especially when it comes to more expensive-to-reach people, like men and the elderly.
    3. Cognitive load bias: Answering an online survey is demanding from a cognitive standpoint, so some people might find the task too difficult to complete, which gets exacerbated by the use of mobile devices. This might result in an under-representation of older people, less-educated or illiterate people or people of a low socioeconomic status.
    4. Self-selection bias: Unlike web panels, with social sampling we have to communicate on the survey subject. People who click on our ads are more inclined to provide answers about a specific topic. As we rarely offer any incentives to respondents, people who complete our surveys do it because it matters to them that their voice is heard. In my opinion, today it’s hard to say what is the lesser evil: having respondents naturally interested in the subject or respondents seeking incentives.

    Reaching the unreachable

    As we witness a new world order emerge as a consequence of the COVID-19 pandemic, surveying people now comes with a set of limitations. Social distance and lockdowns are a no-go scenario for in-person or intercept interviews. People are spending more time than ever online and at home and a third of that time on social media. Again, social sampling here presents itself as a unique opportunity to reach people in impossible places and situations under these circumstances. At Potloc, we launched twin studies in Canada and France about what frontline health workers saw in the trenches against the virus. We reached them in emergency rooms, hospitals, nursing homes and places no one else could enter, at a time where it seemed impossible to get their insights – and with great success. Niche and low-incidence populations are out there, browsing their social media feeds. We just need to find them and offer them the chance to express their opinions.

    Interested in learning more about social sampling and how we run respondent acquisition at Potloc? Check out our public studies at potloc.com/resources or better yet, e-mail us today to schedule a discussion with one of our research experts: hello@potloc.com.

    www.potloc.com
    hello@potloc.com
    1-888-330-3667

      
  • 9 Jan 2021 6:02 PM | Kathy Doering (Administrator)

    Using data from patients’ Facebook pages, a machine learning algorithm accurately predicted which individuals would go on to develop schizophrenia and mood disorders.

    Machine learning facebook data offer insight into schizophrenia

    Source: Getty Images

     Share on Twitter 

     By Jessica Kent

    January 07, 2021 - Data from sites like Facebook and Twitter can reveal a lot about someone’s behavioral health. Past studies have shown that social media activity can predict a person’s demographic characteristics, substance use, and religious and political views.

    Now, researchers have applied machine learning tools to individuals’ Facebook pages in order to determine who would eventually develop schizophrenia spectrum disorders (SSD) and mood disorders – more than a year before the patient’s first hospitalization and official diagnosis.

    In a new study published in Nature Partner Journals Schizophrenia, the team noted that psychiatric symptoms often emerge during adolescence or early adulthood and can interfere with the establishment of healthy social and educational foundations.

    While early intervention efforts can improve outcomes for psychiatric patients, patients’ symptoms often go untreated for months or years before receiving clinical attention. Mental health professionals are looking for new ways to objectively identify early warning signs of emerging psychiatric symptoms to improve early intervention strategies.

    To date, most studies focusing on the associations between social media activity and psychiatric diagnoses relied on assumptions about clinical and diagnostic status. In this study, the team set out to use real patient data with clinically confirmed and validated psychiatric diagnoses to develop machine learning algorithms – one of the first research efforts to do so.

    Researchers analyzed Facebook data 18 months prior to the first psychiatric hospitalization. The group extracted 3,404,959 Facebook messages and 142,390 images across 223 consented participants, with the aim of identifying characteristics that distinguished participants with SSD and mood disorders from healthy individuals.

    The results showed that people with SSD and mood disorders were more likely to use swear words than healthy participants. Individuals with SSD were also more likely to use perception words – like feel, see, and hear – than those with mood disorders and healthy people. Participants with mood disorders used more words related to blood, pain, and other biological processes.

    Additionally, researchers found that the closer participants with SSD came to hospitalization, the more punctuation they used compared to healthy people, while those with mood disorders increased their use of negative emotion words.

    The team also found patterns in image use among study participants: The height and width of images posted by individuals with SSD and mood disorders were smaller than those posted by healthy people, and those with mood disorders posted photos that contained more blues and less yellows.

    The findings demonstrated the ability of machine learning algorithms to identify those with SSD and mood disorders using Facebook activity alone.

    “There is great promise in the current research regarding the relationship between social media activity and behavioral health, and our results published with IBM Research today demonstrate that machine learning algorithms are capable of identifying signals associated with mental illness, well over a year in advance of the first psychiatric hospitalization,” said Michael Birnbaum, MD, assistant professor at Feinstein Institutes’ Institute of Behavioral Science.

    “We have the potential to thoughtfully bring psychiatry into the modern, digital age by integrating these data into the field.”

    Researchers pointed out that social media data, combined with AI and machine learning tools, could play a significant role in mental healthcare in the future.

    “While Facebook alone is not meant to diagnose psychiatric conditions or to replace the critical role of a clinician in psychiatric assessment, our results suggest that social media data could potentially be used in conjunction with clinician information to support clinical decision-making,” researchers stated.

    “Much like an X-ray or blood test is used to inform health status, Facebook data, and the insights we gather, could one day serve to provide additional collateral, clinically meaningful patient information.”

    The study was limited in that some users were more active than others on Facebook, leaving researchers with varying degrees of data. The team also retrospectively collected Facebook archives to use for this analysis. In future work, researchers will need to assess how much data is needed to make a reliable clinical prediction, as well as prospectively monitor participants’ Facebook activity.

    This current study builds on the research team’s previous efforts to show the potential of examining social media and online activity for psychiatry. The group recently published a paper in which they analyzed over 400,000 search queries to identify differences in timing, frequency, and content of searches among individuals with SSD, mood disorders, and healthy people.

    Going forward, social media use could help mental health providers flag emerging disorders.

    “Early diagnosis of serious mental illness significantly improves long term outcomes and treatment responses,” said Kevin J. Tracey, MD, president and CEO of the Feinstein Institutes. “Dr. Birnbaum is pioneering social media and digital clinical strategies to detect illness at the critical early stages when treatments are most likely to be effective.”


  • 28 Dec 2020 5:54 PM | Kathy Doering (Administrator)

    Quirks Media printed an article back in 2016 on this subject that was excellent! We reprinted it here because all the points discussed are still relevant today.

    David R. Morse is president and CEO of research firm New American Dimensions, Los Angeles. Karthik Praveen is co-founder of Consumer Inclusive, a Bangalore, India-based consulting firm.

    For years there was talk about the digital divide between Latino and white consumers. Not anymore.

    According to the Pew Research Center (Figure 1), the share of Latino adults who use the Internet was 84 percent in 2015, up 20 percentage points since 2009, narrowing the gap between Hispanics and whites to just 5 percent. Hispanics, says Nielsen, are among the most likely to own a smartphone, to live in a household without a landline and to access the Internet from a mobile device – nearly three-quarters of Latinos own smartphones, 10 percent higher than the U.S. average, and 10 million watch video on their mobile phones for an average of more than six hours per month.

    Impressive numbers, given that Hispanics now make up 17 percent of the U.S. population, a share that is expected to increase to 29 percent by 2060.

    When it comes to digital, Hispanics are not a segment to be ignored, and social media is no exception. EMarketer reports that in 2015, 76.6 percent of U.S. Hispanic Internet users accessed social networks, compared to 69.4 percent of overall U.S. Internet users. These numbers are projected to increase to 80 percent among Hispanics, compared to 72 percent for the general population.

    On Facebook, by far the most widely-used social media site, 73 percent of all Hispanic adult Internet users have a presence, compared to 71 percent of the total Internet-user population. The gap is even higher for Instagram; while 21 percent of Caucasian adult Internet users are users, 34 percent of all Latinos maintain a presence on the site. A quarter of Latinos use Twitter, compared to 21 percent of Caucasians.

    When it comes to language choice on social media, Hispanics are using both English and Spanish. According to E-consultancy, 33 percent preferred English, while 27 percent opt for Spanish; 40 percent used the two equally. But preference varied with the situation.

    Given the importance of social media for Hispanics, marketers need to keep an active watch on what Latinos are saying about their companies, their brands and the categories that they operate in.

    When doing social media listening with Latinos, the first challenge is to identify those who are posting in English. There is no perfect solution to this but we’ve found that using surname – and sometimes first name – derives a good representation. Second, for those using Spanish, we need to remove those living in Latin America. To do this, researchers should crawl social media sites with social media listening tools to identify IP addresses. We do this in order to ensure that we are only listening to conversations from the U.S.

    The next step is to sanitize the data, by identifying and removing spam, and cleanse the data by identifying and filtering out noise words. Finally, we analyze and tag all relevant social postings for patterns, qualitatively validate them and then bucket them into categories describing topics of discussion and sentiments.

    Social media conversations

    As a case study, we focused on the perceptions and attitudes about heart disease among U.S. Hispanics. We analyzed 9,382 social media conversations between November 2015 and January 2016. Our analysis focused on Twitter, blogs and forums; while heart disease was frequently discussed on Facebook, the majority of conversations were brand-related rather than our primary interest, the challenges and apprehensions people with heart disease encounter.

    When we dug deeply into social media conversations, we found there are that there was a lot of anxiety surrounding heart disease and no shortage of discussions surrounding proactive lifestyle change behavior by the segment. Close to 70 percent of the discussions centered on patients who have already suffered cardiac arrest.

    Both patients and caregivers discussed treatment options like angioplasty and the post-treatment lifestyle changes they underwent. Many were apprehensive about undergoing angioplasty and were looking for alternative treatment options. Many shared the lifestyle changes they underwent following a stroke, such as cycling, exercise and use of fish oil.
    Content sources

    While a third of analyzed social media content originated with patients (Figure 2), half of the discussions were posted by caregivers, relatives and friends, particularly in blogs, perhaps a reflection of the collective mind-set and strong bonds among Hispanics. Much of the content was emotional in nature, offering a telling and very human glimpse of the challenges patients and their loved ones encounter.

    Many patients discussed the symptoms that they suffered before experiencing a stroke, including tight chest, pain in arms and general body fatigue. Patients shared their story along with informative links about what one should do during a cardiac arrest and also lifestyle changes like not skipping breakfast; maintaining their blood glucose and blood pressure levels; weight management; etc. Most patients shared that they went through angioplasty after being diagnosed with cardiac disease.

    Caregivers shared stories of how their loved ones suffered from the condition and how they changed their lifestyle. Some shared that their loved ones became weak after suffering and going through treatment for cardiac related issues. Many inquired about alternate modes of treatment and the cost of treatment. Caregiver conversations that shared lifestyle changes were focused on convincing their loved ones to quit smoking, change the oils they use to cook and to not skip breakfast in order to avoid drops in blood glucose levels.

    When breaking down the different social media platforms, we found Twitter was mainly used to spread awareness about symptoms, treatment options and post-diagnosis care. Users shared links of health care professional and tips about what one should do if he or she suffers sudden cardiac arrest. Many tweets focused on skipping breakfast because of working multiple jobs. Other tweets centered on the cost of treatment.

    Blogs tended to focus on the personal experiences of themselves and their loved ones. Patients mainly described the process that they went through, beginning with the pre-diagnosis stage when they had symptoms like difficulty in breathing, tightness in the chest, etc. Caregivers gave detailed descriptions of how their loved ones had to go through lifestyle changes such as losing weight and changing food habits after suffering a stroke.

    Forums were a platform for expressing opinions and asking questions, including sharing the experiences of suffering from the disease as well as the kind of activities patients undertook because of having heart disease. There were many questions about alternative treatment options to angioplasty as well as the cost of treatment for patients without insurance. Forums such as www.vidaysalud.com were popular online choices for discussions. A frequent concern for users was that some Spanish forums were giving contradictory information regarding treatment.

    Tuning into the conversation

    While many major brands are engaged in social media listening, Hispanics are frequently overlooked, in part due to the challenges imposed by language. However, given the social nature of this consumer segment, social media listening offers an unprecedented opportunity to tune into the content of Hispanic conversations and gain access to a rich panoply of discussion. With a little subjective acumen, social media content can be bucketed and quantified, as well as analyzed for subtlety and nuance. Though it may not be able to provide all the answers, social media listening has its place in the toolbox of any marketer, particularly those looking for insights among Hispanic consumers.



  • 7 Dec 2020 7:12 AM | Kathy Doering (Administrator)

    Social Media Today shares Snapchat's new Levi's partnership. 

    Could this help position Snapchat to lead the way on the next big eCommerce trend?

    This week, Snapchat has announced a new partnership with Levi's, which will enable users to dress up their Bitmoji avatars in classic Levi's outfits.

    Bitmoji x Levis

    As explained by Snap:

    "The Levi’s x Bitmoji collection features timeless Levi’s pieces including the 501 Original Fit Jeans, Trucker Jackets, and Western Shirts, all available in multiple washes. Snapchatters and Bitmoji users can choose between 12 curated Levi’s outfits, or they can customize their look further with billions of unique ways to style the classic pieces."

    Snapchat added the capability to dress up your Bitmoji character in different outfits last year, which has since lead to partnerships with Ralph Lauren and Jordan, among others in creating Bitmoji clothing options.

    Snapchat x Jordan

    Bitmoji characters are hugely popular in the app, with around 70% of Snapchat users engaging with the feature.

    Given this, the option to dress up your custom character in different items of clothing, further aligning it with your personal preferences, has also proven to be a hit - and while seeing your avatar dressed up in new fashion outfits isn't the same as trying those clothes on for yourself, it does help to further brand affiliation, and align consumers with a brand identity.

    But Snapchat's actually now able to go a step further - take a look at this tweet from Snapchat GM Matt McGowan.

    Now, with Snapchat's full-body tracking tools, users can create life-sized versions of their Bitmoji characters, which they can overlay onto real-world scenes. 

    It's not perfect - you can still see the person's real arms and legs overflowing slightly as they move. But it's another way to use Bitmoji characters, and Snap AR, to create a whole new experience. Which also helps to showcase the clothes that your Bitmoji is wearing, and could be a great way to increase brand awareness and connection.

    Like all social platforms, Snapchat has been looking to merge into eCommerce of late, as a means to maximize its revenue potential, and increase user engagement.

    Snap introduced its first 'shoppable' Snap Original shows back in June, and has been working with several brands on new eCommerce integrations, like scannable barcodes and logos and AR 'try on' options, like this integration with Gucci:

    Snapchat AR Try on

    With Facebook and Instagram now pushing their own eCommerce integrations, it makes sense for Snap to also follow suit, as those new activations will change consumer habits over time. Essentially, that means that consumers will eventually come to expect that they'll be able to buy whatever they see in the images and videos shared to their social feeds. The platforms that can best align with this will open up a range of new possibilities for their business tools.

    What's most interesting about Snap, however, is its focus on AR for such purpose, which is where many expect consumer attention to shift in the second half of 2021.


  • 23 Nov 2020 11:18 AM | Kathy Doering (Administrator)

    Blog post from Ann Michaels & Associates ( A research firm that conducts social media research)

    November 23, 2020 by Ann Michaels & Associates

    Competitive Intelligence is something that business has done for decades in one form or another. From mystery shopping to market research using various methodologies, everyone seems to be spying on everyone else. However, many businesses have been slow to consider using social media and online research, for competitive intelligence, as a way to increase market share and to gain an overall competitive edge.

    For the purpose of this blog post, we will zero in on the aspects of using online resources as a way to gain digital competitive intelligence. As artificial intelligence and algorithms continue to perfect, so does the need for good software. Social listening and analytic software options are plentiful and the financial commitment for using them can be huge.

    Listening Platforms, Q4 2020

    According to Forrester, vendors that can provide advanced analytics, brand measurement in visualizations, and broad tech integrations, position themselves to successfully deliver enterprise-wide consumer and social intelligence to their customers (Digimond reports from the study and is named as one of the top software providers).

    Digimind is a Strong Performer

    In 2020, a Forrester’s customer survey found that 59% of respondents incorporate social data into market research data sets, 57% into voice of the customer (VoC) data, and 48% into audience segmentation.

    It is important to mention that while social data plays a significant role, data collection from non-social media data can be equally important.

    Social Media data for competitive intelligence was something we covered in a previous blog.

    According to Hootesuite, social media competitive analysis, includes the following:

    • Identify who your competitors are on social media
    • Know which social platforms they’re on
    • Know how they’re using those platforms
    • Understand how well their social strategy is working
    • Benchmark your social results against the competition
    • Identify social threats to your business
    • Find gaps in your own social media strategy

    Online Research Strategy Steps

    The Importance of Media Monitoring for Businesses on a regular basis with ongoing detailed reporting. Select your brand with at least two top competitors and gather intelligence on a regular basis.

    A Competitor Website is home to a great deal of information that can be used for competitive intelligence. From product and pricing information to new product launches to press releases.

    Review and support sites should be monitored as well. Customers are very vocal online, providing a good deal of detail of product reviews.



  • 20 Oct 2020 12:55 PM | Kathy Doering (Administrator)

    When looking at and vetting social media profiles for authenticity, pay careful attention to the photos! 

    OSINT Research & False Positives

    Posted on October 20, 2020 by eChatter

    StyleGAN

    A great deal of time must be spend on OSINT in order to weed out false positives – good intelligence vs bad intelligence. The degree of reliability and authenticity.  The importance of an accurate starting point is critical when taking your research on a person of interest to the world wide web.

    We will dive into this in more detail in the weeks to come. For now, let’s begin with how to identify a fake photo. Hiding your real identity has never been easier on the web and social media is the scammer’s friend when it comes to this. A photo may be a false positive because while it appears to be the person, in actuality, it is a fake.

    Can You Tell the Difference?

    StyleGanOne is real and one is fake…

    Take a close look at the photos above. One is a real person and one is a computer generated photo. Which is which? Not so easy, right? This is something that all of us in the open source research, law enforcement and private investigations industries will need to be proficient at. A great site to test your skills is Which Face is Real?

    You may wonder how this is even done. You are not alone! Machine learning has been used to customize and generate realistic photos. It is called StyleGAN.

    StyleGAN was originally an open-source project by NVIDIA to create a generative model that could output high-resolution human faces. The basis of the model was established by a research paper published by Tero Karras, Samuli Laine, and Timo Aila, all researchers at NVIDIA.

    (source: https://heartbeat.fritz.ai/)

    What To Look For

    According to Which Face is Real, look for the following things:

    Teeth and Hair: Hair and teeth are very difficult to render realistically. Often teeth are odd or asymmetric. Look for a type of hallo over the hair or other odd imperfections.

    Eye Glasses: Right now, it’s very hard for algorithms to generate realistic-looking eyeglasses. Take a close look at the style of the glasses. Many times one side will look different than the other side.

    Background of the Image: Many times the background of an image is a give-away. Because the concentration is on the face alone, the background may show smudge marks or render unclear.

    When in Doubt….

    Google Image

    If you suspect your target is using a false identity, you can do your very own “fact checking”. Google image will allow you to upload an image to search the web for other images that look just like it.

    One of our recent blog posts discussed this in further detail. Online Research: 3 Tips for Better Results. It is more important than ever to be sure you have the right tools in your tool box.

    PS: If you guess the photo of the woman, you are correct! She is a real person.



  • 25 Sep 2020 3:49 PM | Kathy Doering (Administrator)

    Our social media profiles and activity can reveal a lot about our personalities. Psychology Today's take on the subject!

    By: Gwendolyn Seidman Ph.D.

    Geralt via Pixabay | CC0 license

    Source: Geralt via Pixabay | CC0 license

    The majority of Americans use at least one form of social media. If you're reading this, you probably use social media yourself and have contacts ranging from people you know intimately, like your immediate family and close friends, to people you've met just a few times or haven't had contact within years.

    What can we learn about people from their social media? Despite opportunities to control what we post and curate an idealized image, research suggests that for the most part, social media profiles reflect people's actual personalities, not idealized versions of themselves.

    The Big Five Personality Traits

    A large body of research on social media use and personality has focused on the Big 5 personality traits, the most widely accepted trait theory. When people are asked to rate how much different traits characterize them, those traits cluster into five groups:

    Personality predicts what people do on social media.

    Researchers studying social media and personality often ask users about their behaviors or log users' behavior and determine what correlates with different personality traits. In a meta-analysis, combining the results of more than 30 different studies like this, Lui and Campbell found several patterns. Extraverts tended to spend more time interacting with others on social media. People high in agreeableness tended not to be any more or less social than their less agreeable counterparts, but they did post more photos. Conscientious people tended to spend less time using social media to learn about others and to play games. High openness predicted the opposite pattern of high conscientiousness – More time seeking information about others and more time gaming. Like extraversion, neuroticism was also related to posting more updates and content on social media.

    In addition, research shows that personality relates to the specific types of content people post, as I detailed in an earlier article. Despite the general tendency for social media profiles to accurately reflect personality, there is evidence that these profiles are less accurate for people high in neuroticism, who are more likely to present idealized or less authentic images of themselves.

    Personality predicts the words people use on social media.

    In a fascinating area of study, researchers have used specialized software programs to analyze the language people use in their social media posts. In one such study, researchers used a computer algorithm to determine which words were uniquely related to different personality traits. Words that predicted high levels of extraversion included "love," "night" and "party" – words that reflect social activity or relationships. Those with low levels of extraversion, on the other hand, were more likely to use the words "computer," "I've," and "I don't," reflecting both a greater focus on the self and a preference for activities involving things rather than people.  Highly conscientious people were more likely to use the words "family," "week," and "weekend." These word choices are indicative of their tendency to plan and focus on family responsibilities. People with low conscientiousness were more likely to use swear words, indicating a lack of caution in what they post. Not surprisingly, agreeable individuals used more positive words, and people low in agreeableness used more negative words, especially hostile swear words. Neuroticism was also associated with using negative words, but sadder, rather than angry.

    Other researchers who mine social media data have used frameworks that classify words into categories, rather than looking at word frequency. For example, researchers might organize words into groups like "negative emotions" or "social relations." Not surprisingly, these studies show that extraverts use more words relating to family and social processes. Interestingly, people high in agreeableness tend to talk about food more but talk less about achievement and money. People high in conscientiousness and openness were both more likely to talk about work. This likely reflects conscientious individuals' greater diligence about work and open individuals' greater likelihood of pursuing work they are interested in or passionate about.

    The content on social media predicts personality.

    Researchers sometimes look at the specific content people post on social media. This can include basic profile features, like the number of "likes," the number of friends, or the number of status updates. Bachrach and colleagues found they could predict social media users' levels of extraversion, openness, and conscientiousness from this information.

    Other researchers have found that what people "like" on Facebook is related to their personality. So their preferences for different music or TV shows, products or websites, or even specific types of content posted by friends all relate to personality. In one particularly impressive demonstration of this, Youyou, Kosinski, and Stillwell used people's "likes" to predict their scores on personality measures. Then they compared this to personality ratings provided by that person's friends, family, and work colleagues. The researchers found that "likes" predicted people's personality better than the reports of people who actually knew them.

    So what can we learn about someone's personality from their social media activity?

    The computer algorithm approaches are powerful and suggest that social media companies could know more about you than you think (that's a topic for another day). But ordinary people can also use the insights from this research to understand their social media friends better. Taken to together, these findings suggest that there are a number of factors that could hint at someone's personality:

    • Extraversion: Extraverts are easily identifiable on social media. This is not that surprising, as in offline settings, extraversion tends to be the easiest trait to guess when first meeting someone. Extraverts tend to have more friends, interact with others more, "like" content more frequently, and use more words that reflect social activities.
    • Conscientiousness: Conscientious people are more cautious by nature, and by most metrics, they engage with social media less than their less conscientious counterparts. And when do they engage on social media, they are more likely to talk about work and family.
    • Agreeableness: Agreeable people tend to post more photos. They also tend to opt for more cheerful language, whereas those especially low on agreeableness gravitate toward particularly negative and hostile terms.
    • Openness: For people high in openness, their social media use is likely to reflect their interests. They spend more time using social media as a way to seek information, to talk about their work, or to play games.
    • Neuroticism: Neurotic individuals tend to be more active on social media, much like extraverts. But unlike extraverts, they tend to express more negative emotions in their language, which makes sense given the propensity to experience more negative emotions. And they are especially likely to try to present a more idealized version of themselves.

    While you can't totally judge a book by its cover, or even its social media profile, our social media profiles may reveal more about us than we think.


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