Tag Archives: social media

Harnessing text for human insights #IIeX 

Live note-taking at #IIeX in Atlanta. Any errors or bad jokes are my own.

Chaired by Seth Grimes

Automated text coding: humans and machines learning together by Stu Shulman

  • It is a 2500 year old problem, Plato argued it would be frustrating and it still is.
  • Coders are expensive, it’s difficult at scale, some models are easier to validation than others, don’t replace humans, no one right way to do it, validation of humans and machines is essential
  • Want to efficiently code, annotate coding with shared memoirs, manage coding permissions, have unlimited collaborators, easily measure inter-rather reliability, adjudicate validity decisions
  • Wanted to take the mouse out of the process, so items load efficiently for coding
  • Computer science and HSF influence  measure everything 
  • Measure how fast each annotator works, measure interacter reliability, reliability can change drastically by topic
  • Adjudication – sometimes it’s clear when an error has been made, allows you to create a gold standard training set, and give feedback to coders; can identify which coders are weak at even the simplest task, there is human aptitude and not everyone has it, there is a distribution of competencies 
  • 25% of codes are wrong so you need to train machines to trust the people who do a better job at coding
  • Pillars of text analytics – search, filtering, deduplication and clustering and works well with surveys as well, human coding or labelling or tagging which is where most of their work goes, machine learning – this gives a high quality training set
  • If humans can’t do the labelling, then the machines can’t either
  • Always good to keep humans in the loop
  • Word sense dis ambiguities – relevant – is bridge a game or a road, it smoking a cigarette or being awesome

Automated classification interesting, at scale and depth by Ian McCarty

  • Active data collection is specific and granular, as well as standardized; but it’s slow and difficult to scale, there is uncertainty, may be observer bias via social desirability, demand characteristics, Hawthorne effect [EVERY method has strength and weaknesses]
  • Declared vs demonstrated interests – you can give 5 stars to a great movie and then watch Paul Blart Mall Cop 5 times a 6 months [Paul Blart is a great movie! Loved it 🙂 ]
  • They replicate the experience of a specific URL to generate more specific data
  • Closed network use case – examined search queries from members to recruit them into studies, segmentation was manual and company needed to automate and scale; lowered per person costs and increased accuracy, found more panelists in more specific clusters, normalized surveys if declared behaviors conflicted with demonstrated behaviors 
  • Open network use case: home improvement brand needed a modern shared meaning with customers, wanted to automate a manual process; distinguished brand follower end compared to competitive followers, identified where brand values and consumer values aligned, delivered map for future content creation and path to audience connection

Text analytics or social media insights by Michalis Michael

  • Next gen research is here now, listening, asking questions, tracking behavior, insights experts
  • Revenues don’t reflect expectations, yet.
  • We’re not doing a great job of integrating insights yet, social media listening analytics is not completely integrated in our industry yet 
  • Homonyms are major noise, eliminating them needs humans and machines
  • Machine learning is language agnostic, create a taxonomy with it, a dictionary of the product category using the words that people use in social media not marketing words
  • It is possible to have 80% agreement with text analytics and the human [I believe this when the language is reasonably simple and known]
  • Becks means beer and David beckham but you need training algorithms to do this, Beck Hanson is a singer, you need hundreds of clarifications to identify the exact Becks that is beer
  • Beer is related to appearance and occasions, break down occasions into in home or out of home, then at a BBQ or club
  • What do you say about a beer when they do a commercial that has nothing to do with the beer
  • English has s a lot of sarcasm, more than a lot of other languages [yeah right, sure, I believe you]
  • Break down sentiment into emotions – anger, desire, disgust, hate, joy, love, sadness – can benchmark brands in these categories as well
  • Can benchmark NPS with social media
  • Brand tracking questions can be matched to topics in a social media taxonomy, and there can be even more in the social media version than the survey version

Social media and qualitative – Respect the word! #MRIA16 #NewMR 

Ask first, listen later by Lori Reiser

  • Traditional research often starts with the business, product iterations, product marketing, product fine tuning
  • We should put people first so you hear about unmet needs and pain points
  • Case studies
  • Health insurance firm – young adults getting their first insurance plan, and new retirees moving away from employer benefits; had predefined assumptions but those were based on the six people in the room, fears of these people were financial and health and being bored not really insurance, how did they define good health and how could that be protected, did focus groups and bulletin boards, retirees weren’t worried about getting sick but rather that their parents would get sick, younger people were more worried about stress as their health issue
  • Meat company – what did consumers need in terms of communication needs, saved qualitative for the end of the research, started with a survey of staff members and inspection organizations, realized they needed to formalize their email address to clients so that it didn’t come from Annie Pettit but rather from the company, realized that Mennonite members didn’t have email addresses [pay attention to that anyone who says they do probability sampling via RDD]
  • Pharmacist – surveyed pharmacists as well as focus groups and the focus groups were after the fact, what does patient centered care mean, many barriers in terms of how pharmacists communicate with people given what doctors and other people want them to be able to say
  • You can’t ask broad questions unless you go qualitative, open ends on a survey arne’t going to cut it; give your users permission to participat in the idea making, find the trendsetters and listen to them, use skilled moderation

Classified: Research that integrates to innovate by Mark Wood

  • Technology has given us an identify crisis, people challenge are traditional beliefs, anyone can do DIY research, other people are jumping into our sandbox with new types of data
  • Tactics to get our mojo back
  • Understand consumer dynamics in a more connected world
  • Leverage expertise in a data curation to improve SML capabilities, Think both/and between traditional survey and SM, Help companies navigate path to purchase, use data to help action
  • Have to work with clients better and bring in other pieces of data so we can inform them better
  • Bringing MR expertise into social media listening
  • We need to take SM data to the full extent just not report facts and figures
  • Must get access to this data first and then we can sample and structure and clean it
  • SM provides an authentic voice of the consumer, has rich detail; surveys enhance social media structure to categorize themes and related back to real initiatives 
  • Use social and survey together to inform each other
  • Need to identify lots of buzz with lots of impact, not just lots of buzz
  • Use buzz impact matrix to understand which conversations have high buzz, high impact, and then dive deeper into those issues
  • Identify all the touch points that need to be assessed, identify which have the highest reach, but there are big differences in claimed versus reality
  • Need to move from measurement to action [the problem of the century!]
  • Opportunities are greater than ever for MR to have an impact

Social noise – cacophony or symphony #MRSlive @TweetMRS #MRX 

Live blogged at MRS in London. Any errors or bad jokes are my own.

The art of noise by Tom Ewing

  • #IPAsocialworksinitiative – to guide effective use of social media data
  • It’s all about measuring not counting, Ray Poynter wrote this part
  • The insight guide  is being written by Tom Ewing and he is interviewing people for it
  • Five basic questions
  1. What questions do you need to answer, what decisions will betaken because of it
  2. What do you know already, existing research, behavioural
  3. What social behaviora are you looking for, what data sources, do you need aggregate data or granular level
  4. What is the relevant timescale, ad hoc or continuous, how do you know yyou’re finished
  5. Do you need quant metrics, what are they, it’s more than likes follows
  • We have reached the peak of social tech
  • Seth Grimes says the state of social insight is “confused,” it’s not really a mature technology, widely adopted, but not fully integrated
  • It’s the early majority now, tactical, silos, unstructured text, the future is here but it is unevenly distributed
  • We need to clear out the cliches, integrate with methodologies, integrate with insights and business and people 
  • Different poll results would arise if you use Twitter vs Facebook [i see this as a sampling problem, you don’t just take any church or school or company and say it is representative]
  • UK Facebook data is closer to a census than a sample [but it is still very much a sample!]
  • You can join insights with other methodologies [data fusion is ALWAYS wise, every method reveals different insights]
  • Provide more file and predictive tracking systems and an ability to get granular and specific
  • Who owns social insight? Is it marketing? Analytics? Insights? PR? Sales? It’s more about collaborating  [why must one group OWN it, everyone can benefit hugely from it]
  • Finding common ground – we’re all working toward the same goal, emotional understanding of people
  • Limits of real time means it’s more tactical but there is indeed strategic value
  • How do you get insight about a topic when you know nothing about it [oh goodness, I could go on about this. I was asked to draw insights about cars and trucks. I know NOTHING about them and couldn’t understand anything people were talking about. Expertise in the topic is a MUST! Put me on the food/outdoors/music research.]
  • AI is already doing so much work that people would have done – collecting data, sorting and coding, analyzing, prepping, reporting
  • Social insight begins with social practice, use new platforms like Whatsapp and snapchat, look beyond the brand level to the topic level, consider pictures and video, look for patterns at the network level
  • Different things come out via text and images but you wno’t know unless you plan and look for differences in different types of content
  • We are working towards general use, stratégie, cooperation, seamless integration among people, rich media as well as unstructured text
  • Tom asks people to submit their social media case studies to him for publication in the book

Finding insight in 140 characters by Jake Steadman

  • Jake [not from Statefarm] speaks
  • Story about Star Wars, in 1977, need to tap into mainstream media, tap into core group of fans, went on TV and publications. FOr second movie he went to com icon. Fans went in the hundreds to see them in person for Q and A.
  • Today, mobile is eating other media time.everyone has a mobile phone. December of last year, new Star Wars came out. Still need media and interest and fan base. THey launched on Twitter. That tweet drove all the other media. Drove coverage in print. Access to the stars still applies but they did it more directly and personal on Twitter. Stars did this on the red carpet, backstage, White House visits, all on Twitter. 1.2 billion tweets on opening weekend.
  • All social data can drive insight
  • There are culture issues and there are tools. 
  • Rise of the machines, machines allow you to become storytellers and consultants, it allows you to be a leader not a methodological policeman
  • Let’s you do same day insights and be agility, we need to get over our obsession with precision, forget statistical precision [agreed, don’t create precision with decimal places, know when your data is directional and don’t make it more than it is ]
  • Social is the democratization of data, client side is more like to be using social, agencies are more likely to be using big data, agencies need to be more for less and quicker
  • Look for your soggy fries – customers were starting be less loyal with a restaurant, you could run a large research project, or you could look at social data immediately, found many uses of the word ‘soggy fries’, it didn’t need precision but rather it needed recognition

Panel with Jenny Burns, Christopher Wellbelove, Jess Owens, James Devon

  • Some people jump at social media because it’s cheaper than things like focus groups [be cautious, cheaper means you need to spend more time thinking and analyzing it]
  • Lots of people are analyzing social media without ever using it, you need to use the tools to really understand them [the speaker has now gone through three pairs of google glasses, and might be tweeting as we speak 🙂 ]
  • Social media is still treated as a slightly dangerous cousin
  • 67% of people using social media puts it really into late adoption, it is not new nor early adopter territory 
  • It says more about the market research industry being years behind to be so late in using this technology
  • Privacy and ethics still matter, some companies get individual permission to review Twitter accounts
  • People need to understand how their data is being used, whether it’s aggregated, Facebook data is fully anonymized and aggregated and great for ethics and privacy

[I kind of like have a couple presentations followed by a separate panel]

  

    Keynote: Why Social Media “Likes” Say More Than You Might Think by Dr. Jennifer Golbeck, Human-Computer Interaction Lab, University of Maryland #ISC2015 #MRX

    MRALive blogged from the 2015 MRA Insights & Strategies Conference, June 3-5, 2015 in San Diego. Any errors or bad jokes are my own.

    • how much do two strangers online trust each other? you need to know about the people themselves first.
    • social media data can give you accurate data, even when used in a simple way
    • can predict introversion, political leaning, procrastination, personal health habits from your posts
    • likes on facebook are always public, can use this to predict many things
    • top four likes most indicative of high intelligence include science, thunderstorms, colbert report, and liking the page for curly fries. For low intelligence, the like was for the page “i love being a mom” But these don’t truly relate to intelligence.
    • homopholy – we are friends with people who are like us, our traits are more common among friends than among random people.
    • you just need one smart person to like a page and then it spreads like a virus to all your friends
    • we’re really good at predicting sexual orientation, even in places where being gay could get you executed
    • how does a store like Target figure out you’re pregnant, not from pregnancy tests, – an extra bottle of vitamins, a bigger purse, brightly coloured rugs together are a statistical connection
    • how can you know what these statistical combinations are?
    • can your social media network figure out which friend is your spouse? you know which friends are friends with each other and nothing else. Often it is the person with the most friends in common. But look at social dispersion instead, eg., your sports friends, your school friends, your family friends, your work friends. Dispersion is who is connected to the most of your groups – that is the spouse about 75% of the time. the other 25% is a good indicator that youre going to break up your relationship
    • can predict postpartum depression from social media content.
    • how easy is it to get data?
    • takethislollipop.com – makes a video out of your social media accounts, try it if you think all your settings are private
    • we leak a lot of data, we don’t realize how much data apps are pulling
    • it’s not all bad – apps recommend products you might like, google uses it to make the web easier to interact with
    • we don’t have control over it – don’t know who has data or what they’re doing with it
    • even though the algorithms are smart, we still don’t buy whatever the algorithm says we might like. but they tell us things we would never think about but we actually want
    • treat your business algorithms as useful but realize some are wrong or shouldn’t be acted on, it’s one more piece of advice
    • [jen needs no slides, she changes every 5 or 10 minutes just for the heck of it, impressive]
    • how do you figure out which people like the targeting or don’t like the targeting
    • you don’t want to be the creepy facebook stalker guy, it needs to be handled with care

    Why won’t I Link In with you?

    I’m pretty open to new connections. First of all, I’m the Editor In Chief of a marketing research magazine called Vue so I am always in search of new connections who could be potential authors (could you?). Second, I know that the future isn’t written in stone and I could be unexpectedly job hunting tomorrow. In both cases, the more connections the better.

    At the same time however, I do not Link with every Tom, Chris, and Susan who asks. I am not a LION. My criteria may be broad but they are simple.

    1. Are you a person? There is a new trend of creating LinkedIn profiles for companies as opposed to people. I refuse to link with companies. I can’t have a conversation with a company. I can’t debate a new ethical issue with a company. I can’t ask a company for its perspective on a case study. Sorry. No wait. Not sorry at all. I only link with human beings.
    2. Are you in my field? I love to link with marketing researchers in all walks of life. But if you’re in a related field, that works for me too. So, marketers, advertisers, neuroscientists, ethnographers, statisticians, field managers, data scientists, linguists, community managers, moderators, and more all meet my criteria. All of these types of people have an abundance of unique and valuable skills that Canadian researchers could learn from in a magazine article.
    3. Have we met before? No worries, that doesn’t matter to me at all. You can’t help it if you live in Australia and I live in Canada, and there’s no way our paths will ever cross. I value expertise not geography.
    4. Is your profile filled out? I examine the profile of every single person who requests to link with me. Some profiles are completely empty or have just a couple of job titles. It’s nearly impossible to figure out whether we could have a meaningful conversation about surveys or data or charts. For all I know, you created the profile today and have no intention of coming back. Since LinkedIn limits the number of connections you can have, it doesn’t make sense to Link with someone you will never see again. Come back when I can make an informed decision.
    5. Did you welcome me with a sales pitch? LinkedIn is indeed a social network for business people and an important place for creating new business relationships. But there is no need for your first message after linking with me to be a dissertation on how you are guaranteed to provide me with the best product ever and we need to talk immediately to outline our amazing new partnership. I will unlink you before I finish deleting your welcome message. Chat with me first, share a blog post, ask for opinion, let me get to know you. You might just find that I ask YOU about your services and that’s a far better business bet.

    Go ahead. Try me.

    I Am Your Stinky SeatMate

    With more than twelve hours of flying time and four hours of layover time ahead of me, it was difficult to look forward to a conference where I would give a presentation on social media research to hundreds of people. However, given that the trip would land me in the 13 century city of Stockholm, with its cobblestone streets, ancient palaces, and stunning architecture, the impending cramped legs and utter boredom seemed worthwhile.

    My journey began in the Canadian prairies when I parted with my checked luggage at the Saskatoon airport. My luggage immediately headed westbound to Edmonton, a city not even on my eastbound itinerary, and I, after numerous flight delays and a subsequent cancelation, headed back to a hotel room overlooking a garbage dumpster. Leaving for Stockholm would have to wait another 24 hours.

    As a vocal marketing researcher who specializes in social listening research, I’ve taken careful steps to maximize my online exposure to as many relevant colleagues as possible. More than seven thousand professionals follow my Twitter account where I share my thoughts about how to conduct high quality social listening research. More than a thousand people have friended my Facebook account, a place where I share some of my marketing research thoughts but far more personal thoughts, opinions, and rants. Nearly four thousand people have connected with my LinkedIn account, a social network for professionals and business people, many of whom travel – a lot.

    What does that mean? It means that more than seven thousand people on Twitter, plus the thousands of people they shared my tweets with, were exposed to my frustrations via tweets labeled @AirCanada, #IAmYourStinkySeatMate, and #LostLuggage. On Twitter, I shared the fact that my ‘free’ breakfast voucher did not cover the cost of a basic breakfast. I shared images of the highly fragrant toiletries I received but could not use, including an advertisement for the toiletries themselves. I shared my disappointment in not also receiving a t-shirt (easy resolution), socks (easy resolution), or underwear (Yes, I’ll admit, difficult.). Since tweets are public, and they are now searchable in social media listening results and Google search results for years to come, I was careful to maintain a mild level of professionalism during my frustrations.

    On the flip side however, Facebook has a higher degree of privacy than Twitter. In the best case scenario, only the thousand people I am friends with on Facebook will ever see what I post there. It is there, on Facebook, that a thousand of my closest friends listened, watched, and sympathized with how I really felt. On Facebook, my close friends and family, the people who are most influenced by my personal opinions and brand experiences, listened as I bemoaned how my luggage was lost before I even saw an airplane. They sympathized as I wandered from airport to airport, from help desk to help desk, asking agents for the whereabouts of my luggage. Thousands of people saw the brand name Air Canada next to phrases like “Your bag probably fell off the line” and “We can’t seem to locate your luggage but it will probably be in London.” My friends and family saw images of the pathetic hotel room I was given, and 6 second Vine videos of toiletries that I couldn’t use because they weren’t what my doctor recommended.

    It wasn’t only Air Canada that failed me though. There were many opportunities for other companies to become knights in shining armour. A desperate tweet to Aveeno led nowhere. No tweets of sympathy, no surprise package waiting for me at the end of my journey. And oh, how I longed for clean socks and underwear, precious items nowhere to be found in the airports. A tweet to Hanes resulted in no sympathy tweets nor offers to supply the items either. Though fellow tweeters also shared my call for assistance with their thousands of followers, nothing happened. I could have been profusely praising Aveeno and Hanes right now but, rather, I am sharing my disappointment in a very public forum.

    But let’s ignore the cancelled flight and lost bags for a moment. What were Air Canada’s biggest fails, the reasons that I ended up being so vocal?

    They passed the buck. They expected me to find and speak to the right person after getting off an eight hour flight. They should have done the speaking for me. They have the computer system in front of them. They know the right people to talk to. They know how all the airports and airlines work. They should have greeted me at my next connection with a message updating me on status of my lost luggage. Instead, I tweeted.

    They chose the wrong language. They “invited” me to speak with an agent on my arrival at a strange airport in a foreign country. Perhaps I misunderstood, but I was not begin invited to a birthday party. They seemed to have forgotten who made the mistake. So I Facebooked my disappointment.

    They chastised me. With a presentation to hundreds of my colleagues on the horizon, forgive me when I do anything I can to find the luggage with my presentation clothes and shoes. Of course I send both tweets and Facebook messages to Air Canada. There was no need to slap my hand with a patronizing comment that my messages had already been answered elsewhere.

    And on that note, have you heard about Chester the Cat? Hundreds of retweets later, thousands of sympathic followers later, and millions of highly memorable and salient social media impressions later, Chester the Cat was finally found on June 18, 2014 after being lost by Air Canada for an entire month. Skinny but alive. I’m glad I only lost my luggage.

    Social media is killing social

    If you subscribe to the Myers Briggs theory of personality, introversion/extroversion is a personality trait that looks like a normal curve. Half of people are introverts and half of people are extroverts. Indeed, this trait is a continuum such that people aren’t simply one or the other. Everyone has some degree of extroversion and introversion, and the ratio differs from person to person. But let’s press on.

    White Noise: A Cautionary Musical

    How is social media killing social? Well, people are spending more and more time pulling those little electronic devices out of the purses and pockets and typing on them. Instead of meeting up with their friends, going to a coffee shop, and chatting in person, people are simply pulling out their phone and texting, or tweeting, or facebooking those conversations. And instead of lengthy, well-laid out conversations, they’re sending out quick sounds bites and pithy remarks all with the intent of getting a chuckle out of someone else sitting on their couch waiting for a pithy remark to respond to.

    Is this reality? Maybe. If you’re an extrovert. But if you’re an introvert, it could very likely be a completely incorrect picture. You see, introverts don’t require the constant noise of five people talking over each other to entertain themselves. Introverts put up with all that noise because half of the world is extroverted and they don’t know how to be quiet for five minutes.  Introverts have no need to constantly flap their lips and make noise and listen to themselves talk. When possible, introverts will simply avoid all that nonsense. It’s easier, it’s quieter, and it doesn’t create unnecessary white noise.

    If you think about it, social media creates a quiet place where people can talk to each other without interrupting five other people who are also trying to fill their air with their noise. Social media creates a space where introverts want talk. A place for people who would have never talked in a crowd before can now share their opinions in a calm and quiet place. Social media creates a place for people who might have never shared their opinion before to share their thoughts with many different people. Social media is a tool that just so happens to increase the sociability of introverts. A place for them to meet people they would have never met otherwise. A place to make friends with people they would have never met otherwise.

    Is social media killing social? Maybe if you’re an extrovert. But absolutely not if you’re an introvert. And the world could stand to listen to the other 50% of people for a change.

    How to run a great webinar

    Web conferencing: great way to get a bunch of ...

    What makes a great webinar, you ask? Well, of course there’s a top ten list for that!

    1. Write a script: Don’t you dare read an in-person presentation. No! No! But with the tight timelines of webinars, you can consider this option. It will ensure you stay exactly on time and cover every important point. But re-read points #2 and #3.
    2. Engage don’t read: It’s ok to read a script but it’s not ok if I can tell you’re reading. Read as if you were actually talking. Keeps the ums and ahs that you would normally say, though perhaps cut back on them if you’re an abuser.
    3. Voice modulation:  Nothing makes people tune out quicker than a monotone voice. Make sure your voice rises and falls and pauses and speeds up as you normally would. If you can’t fake it, then bring some colleagues into the room and present your webinar to them.
    4. Don’t go under time: Don’t run short. Webinars are often only 30 minutes total and you should use up the entire 20 minutes of speaking time (allowing for 10 minutes of questions). 15 minutes feels too short and almost like I shouldn’t have bothered to break up my schedule for you. 20 minutes feels like you wanted to give me as much as you could.
    5. Don’t go over time: Your audience was kind enough to loan you 30 minutes, not 32 minutes, and certainly not 35 minutes. I don’t care how excited you are about the questions coming in. Close on time. You can follow up on individual questions and answers by phone, email, twitter, or otherwise.
    6. Budget time for each slide: Assume your system will take 1 to 5 seconds for viewers to see your slides change. Make sure your talk budgets 5 spare seconds on either side of each slide. In other words, don’t rush through 100 slides in 20 minutes. A good guide is no more than 1 slide per minute.
    7. Forget the transitions: Fancy slide transitions and builds are great for in-person presentations but are fodder for failure in a webinar. Every image change adds technology time to transfer the image across the wires and adds one more permission point for glitches. Simple=Fewer problems.
    8. Make a point: Again, assuming technology will glitch, make sure a written point is made on each slide. Pictures are pretty but when your phone cuts out for 10 seconds, the entire point of a slide can be lost if there is no guiding text.
    9. Have a back channel: Whether it’s Twitter and a hashtag, your online community, or the webinar system itself, give the audience a back channel to talk among themselves. Let them talk to other people who are just as interested in your talk as you are. It’s networking and education all in one.
    10. Get feedback: If you can’t bear to listen to or watch the video afterwards, ask your colleagues to be bluntly honest. Could they tell you were reading? Was your voice interesting? Did you time the slide transitions and your words well?

    How low will you go: 5 of my personal social media rules

    It’s very easy to stick your foot in your mouth when you go online. You can get caught up in the moment and before you know it, you’ve said something you wish you had never said, something that you’ve never imagined you could say. With that in mind, I have a few rules that I try to follow. I’m sure that on occasion I’ve slipped, but here is what I strive for.

    1. happy kid from IranI won’t use profanity or crude language. I have used a choice word now and then but to write it in the online space where it will live on in perpetuity doesn’t work for me.
    2. I won’t name people on a website if they aren’t already using the website. In other words, if a friend doesn’t use Twitter, then I won’t talk about them on Twitter. The only exceptions are very public people, like Barack Obama, Pete Cashmore, or Katy Perry.
    3. I won’t criticize individual people online. Ideas, yes. Companies, yes. Organizations, yes. People, no.
    4. I won’t release personal details of other people online. That includes other people’s email addresses, the city they live in, names of their kids.
    5. I won’t share pictures of children that people make fun of, even when no name is attached to the photo and the child is seemingly anonymous. The kid probably didn’t give permission for the photo, they’re not old enough to give permission to use the photo, and they’re not old enough to understand the consequences of distributing the photo. (Think memes here.)
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