Context

The Stanford Dogs dataset contains images of 120 breeds of dogs from around the world. This dataset has been built using images and annotation from ImageNet for the task of fine-grained image categorization. It was originally collected for fine-grain image categorization, a challenging problem as certain dog breeds have near identical features or differ in colour and age. I have used only images, so this does not contain any labels .

  Content

Number of images:… See the full description on the dataset page: https://huggingface.co/datasets/ksaml/Stanford_dogs.

Here are a few use cases for this project:

1. Dog Identification App: "dddog" can be used to build an app that helps users identify various dog breeds from images. This can be useful for pet owners, vets, or enthusiasts who wish to get detailed information about a specific dog breed.

2. Enhanced Security Surveillance: The model can be used in security cameras or surveillance systems, where it can identify and separate movement instances of a dog or a human. The information can be valuable in ensuring security in home or public spaces.

3. Animal Control & Welfare: Animal control agencies can use this model to track and monitor dog populations in various cities. They can identify both stray dogs and dogs with owners, helping with planning and executing animal welfare policies.

4. Augmented Reality Games: Developers can use this model for AR games where users need to identify or interact with virtual dogs or humans in real-world environments.

5. Smart Pet Doors: The model can be used in the development of "smart" pet doors which only operate when detecting a specific type of animal (dogs in this case) approaching, preventing unwanted animals from entering the house.

A large set of images of cats and dogs. There are 1738 corrupted images that are dropped.

To use this dataset:

import tensorflow_datasets as tfds

ds = tfds.load('cats_vs_dogs', split='train')
for ex in ds.take(4):
 print(ex)

See the guide for more informations on tensorflow_datasets.

https://storage.googleapis.com/tfds-data/visualization/fig/cats_vs_dogs-4.0.1.png" alt="Visualization" width="500px">

Context

With this dataset we hope to do a nice cheeky wink to the "cats and dogs" image dataset. In fact, this dataset is aimed to be the audio counterpart of the famous "cats and dogs" image classification task, here available on Kaggle.

Content

The dataset consists in many "wav" files for both the cat and dog classes :

• cat has 164 WAV files to which corresponds 1323 sec of audio
• dog has 113 WAV files to which corresponds 598 sec of audio

You can have an visual description of the Wav here : Visualizing woofs & meows 🐱. In Accessing the Dataset 2 we propose a train / test split which can be used.

All the WAV files contains 16KHz audio and have variable length.

Acknowledgements

We have not much credit in proposing the dataset here. Much of the work have been done by the AE-Dataset creator (From which we extracted the two classes) and by the humans behind FreeSound From which was extracted the AE-Dataset.

PS: the AE-Dataset has a policy saying you can mention them: Naoya Takahashi, Michael Gygli, Beat Pfister and Luc Van Gool, "Deep Convolutional Neural Networks and Data Augmentation for Acoustic Event Recognition", Proc. Interspeech 2016, San Fransisco.

Inspiration

You might use this dataset to test raw audio classification challenge ;)
A more challenging dataset is available here

Dataset used in the article "Does Visual Stimulation by Photographs of Cats and Dogs Make People Happier and More Optimistic?"ColumnsIDis_preview: true - response by the researcher to check the questionnaire, it should be removedremove: respondent checked that his/her responses are not valid and should not be used in future analysisfinished_proc: percentage of the questionnaire finisheddate_time: filing of the questionnaire started at this timeduration_formatted: duration of the filling of the questionnairebrowserbrowser_versionOS: operating systempriming: true - primed group, false - control groupcat_dog: objects on photos showngenderage: in yerssex_o: attraction to people of the opposite sex (scale 1 - 7)sex_s: attraction to people of the same sex (scale 1 - 7) orientation: computed as the difference of previous twomood: actual mood (scale 0 - 5)condition_phys: physical condition (scale 0 - 5)condition_psych: mental condition (scale 0 - 5)life_quality: life quality (scale 0 - 5)optimism: mean of previous threeoptimism_zskore: z-score of the previous children_own: how many children does respondent havewanted_sons: total number of sons which respondent would like to havewanted_daughters: total number of daughters which respondent would like to havewanted_children: a sum of previous twoliking_dogs: how much respondent likes dogs (scale 1 - 100)present_whenever_dog: respondent has ever kept a dogpresent_now_dog: respondent keeps dog nowpresent_Ndogs: how many dogs does respondent keep now liking_cats: how much respondent likes cats (scale 1 - 100)present_whenever_cat: respondent has ever kept a catpresent_now_cat: respondent keeps cat nowpresent_Ncats: how many cats does respondent keep now

This dataset is about books. It has 3 rows and is filtered where the book is Alpha dogs : how political spin became a global business. It features 7 columns including author, publication date, language, and book publisher.

BackgroundDog rabies annually causes 24,000–70,000 deaths globally. We built a spreadsheet tool, RabiesEcon, to aid public health officials to estimate the cost-effectiveness of dog rabies vaccination programs in East Africa.MethodsRabiesEcon uses a mathematical model of dog-dog and dog-human rabies transmission to estimate dog rabies cases averted, the cost per human rabies death averted and cost per year of life gained (YLG) due to dog vaccination programs (US 2015 dollars). We used an East African human population of 1 million (approximately 2/3 living in urban setting, 1/3 rural). We considered, using data from the literature, three vaccination options; no vaccination, annual vaccination of 50% of dogs and 20% of dogs vaccinated semi-annually. We assessed 2 transmission scenarios: low (1.2 dogs infected per infectious dog) and high (1.7 dogs infected). We also examined the impact of annually vaccinating 70% of all dogs (World Health Organization recommendation for dog rabies elimination).ResultsWithout dog vaccination, over 10 years there would a total of be approximately 44,000–65,000 rabid dogs and 2,100–2,900 human deaths. Annually vaccinating 50% of dogs results in 10-year reductions of 97% and 75% in rabid dogs (low and high transmissions scenarios, respectively), approximately 2,000–1,600 human deaths averted, and an undiscounted cost-effectiveness of $451-$385 per life saved. Semi-annual vaccination of 20% of dogs results in in 10-year reductions of 94% and 78% in rabid dogs, and approximately 2,000–1,900 human deaths averted, and cost $404-$305 per life saved. In the low transmission scenario, vaccinating either 50% or 70% of dogs eliminated dog rabies. Results were most sensitive to dog birth rate and the initial rate of dog-to-dog transmission (Ro).ConclusionsDog rabies vaccination programs can control, and potentially eliminate, dog rabies. The frequency and coverage of vaccination programs, along with the level of dog rabies transmission, can affect the cost-effectiveness of such programs. RabiesEcon can aid both the planning and assessment of dog rabies vaccination programs.

IntroductionThe aim of this study was to determine patterns of physical activity in pet dogs using real-world data at a population scale aided by the use of accelerometers and electronic health records (EHRs).MethodsA directed acyclic graph (DAG) was created to capture background knowledge and causal assumptions related to dog activity, and this was used to identify relevant data sources, which included activity data from commercially available accelerometers, and health and patient metadata from the EHRs. Linear mixed models (LMM) were fitted to the number of active minutes following log-transformation with the fixed effects tested based on the variables of interest and the adjustment sets indicated by the DAG.ResultsActivity was recorded on 8,726,606 days for 28,562 dogs with 136,876 associated EHRs, with the median number of activity records per dog being 162 [interquartile range (IQR) 60–390]. The average recorded activity per day of 51 min was much lower than previous estimates of physical activity, and there was wide variation in activity levels from less than 10 to over 600 min per day. Physical activity decreased with age, an effect that was dependent on breed size, whereby there was a greater decline in activity for age as breed size increased. Activity increased with breed size and owner age independently. Activity also varied independently with sex, location, climate, season and day of the week: males were more active than females, and dogs were more active in rural areas, in hot dry or marine climates, in spring, and on weekends.ConclusionAccelerometer-derived activity data gathered from pet dogs living in North America was used to determine associations with both dog and environmental characteristics. Knowledge of these associations could be used to inform daily exercise and caloric requirements for dogs, and how they should be adapted according to individual circumstances.

Context:

This dataset contains survey responses to a survey that people could complete when they signed up for the 5-Day Data Challenge.

On December 12, 2017 survey responses for the second 5-Day Data Challenge were added. For this version of the challenge, participants could sign up for either an intro version or a more in-depth regression challenge.

Content:

The optional survey included four multiple-choice questions:

1. Have you ever taken a course in statistics?

• Yep
• Yes, but I've forgotten everything
• Nope

1. Do you have any previous experience with programming?

• Nope
• I have a little bit of experience
• I have quite a bit of experience
• I have a whole lot of experience

1. What's your interest in data science?

• Just curious
• It will help me in my current job
• I want to get a job where I use data science
• Other

1. Just for fun, do you prefer dogs or cat?

• Dogs 🐶
• Cats 🐱
• Both 🐱🐶
• Neither 🙅

In order to protect privacy, the data has been shuffled (so there’s no temporal order to the responses) and a random 2% of the data has been removed (so even if you know that someone completed the survey, you cannot be sure that their responses are included in this dataset). In addition, all incomplete responses have been removed, and any text entered in the “other” free response field has been replaced with the text “other”.

Acknowledgements:

Thanks to everyone who completed the survey! :)

Inspiration:

• Is there a relationship between how much programming experience someone has and why they’re interested in data science?
• Are more experienced programmers more likely to have taken statistics?
• Do people tend to prefer dogs, cats, both or neither? Is there a relationship between what people prefer and why they’re interested in data science?

List of dogs registered in Adelaide City Council area (Adelaide and North Adelaide) for a particular period. Information provided includes dog name, breed, period, gender, current status, class, transaction type and suburb. Note: Normal – means one dog registered to the property. Normal multiple – means there is more than one dog registered (2 or more dogs).

April 2025 These data-sets, and the associated MPS Stolen Animals Dashboard, are no longer being updated. The data used in the MPS Stolen Animals Dashboard Data is available here MPS Stolen Animals Dashboard Data - London Datastore, along with the related data definitions. Please note that, this data set is running monthly, a month in arrears. The data shows a count of stolen animals as shown on the dashboard linked below (including count, borough, pet type, recover, year/ month and the offence type). The count is calculated by the pet count so there may be one offence/ crime record of dogs stolen, but if there were three dogs stolen during the offence then we will use the pet count of three.

This is part of VGGSound dataset with everything related to cats and dogs converted to 10 seconds 16kHz mono wav. I made it for my University research, because original dataset is kind of huge :)

There are also two csv files with train/test split collected from VGG Sound splits. All data numbered according to indexes of original csv tables.

Each line in the csv file has columns defined by here: Index in original VGGSound (my addition), YouTube ID, start seconds, label, train/test split.

Also, some of the video links (~800 of them) in tables lead to unavailable videos (age restricted/deleted/etc.), which was not downloaded and therefore is not here – so there would be no audio for some indexes.

The example of real practice use of the dataset can be found in my VQ-VAE 2 notebook 👨‍💻. I've also got this helper notebook 🐱🐶 which shows some simple actions you can do with audio dat. In particular: - Some of the audio files are 9 seconds long – how to pad it - How to prepare spectrograms to use them as regular pictures

And umm I could not figure out how to do a proper citation, but here it is from original VGGSound

@InProceedings{Chen20,
 author    = "Honglie Chen and Weidi Xie and Andrea Vedaldi and Andrew Zisserman",
 title    = "VGGSound: A Large-scale Audio-Visual Dataset",
 booktitle  = "International Conference on Acoustics, Speech, and Signal Processing (ICASSP)",
 year     = "2020",
}

IntroductionChronic kidney disease (CKD) in canines is a progressive condition characterized by a gradual decline in kidney function. There are significant gaps in understanding how CKD is managed in canines and the full extent of its impact. This study aimed to characterize disease management of CKD and its impact on dogs, their owners and the veterinary healthcare system in the United States of America (United States).MethodsData were drawn from the Adelphi Real World Canine CKD Disease Specific Programme™, a cross-sectional survey of veterinarians, pet owners and their dogs with CKD in the United States from December 2022 to January 2024. Veterinarians reported demographic, diagnostic, treatment, and healthcare utilization data, for dogs with CKD. Owners voluntarily completed questionnaires, providing data about their dog, as well as quality of life and work-related burden using the Dog Owners Quality of Life, and the Work Productivity and Activity Impairment questionnaires. Analyses were descriptive and Cohen’s Kappa was used to measure agreement between owners and veterinarians.ResultsA total of 117 veterinarians provided data for 308 dogs, of which 68 owners also reported information. Discrepancies in recognizing symptoms of CKD in dogs, particularly excessive water consumption and urination, were identified between veterinary professionals and owners. Interventions for managing CKD in dogs focused on controlling symptoms and supporting kidney function through dietary modifications and medication. Owners of dogs with CKD reported minimal impact to overall work and activity impairment (10 and 14%, respectively). At diagnosis, 78.6% of dogs were International Renal Interest Society Stage I-II, and 21.5% were Stage III-IV. Regardless of CKD stage, owners strongly agreed that ownership provided them with emotional support and companionship. Regarding veterinary healthcare utilization, 95% of dogs were seen in general veterinary practices.DiscussionThese findings emphasize the value of real-world evidence in enhancing our understanding of CKD in companion animals and informs future strategy for the real-world diagnosis and treatment of CKD. The results also provide insights to the potential burden experienced by owners of dogs with CKD.

Background

The first-ever, large-scale generative modeling research competition, Generative Dog Images, was held on Kaggle in the summer of 2019. Over 900+ teams participated and submitted a total of 10k+ generated samples, 1.6k of which were selected as the final submissions to rank on the private leaderboard. We are releasing the competition submissions as an effort to facilitate research on generative modeling metric design, particularly towards tackling the issue of detecting training sample memorization, intentional or not.

Content

Each competition submission consists of 10k generated samples of dog images from a generative model trained on the Stanford dogs dataset. As expected participants are incentivized to optimize for the objective and many exploited the insensitivity to training sample memorization issue of current popular generative modeling metrics (e.g. IS, FID). We provided manual labels of the type of intentional memorization technique adopted (if any) for each submission. Details regarding the labels can be found in the description of the labels.csv file. We also provided human-assessed image quality annotations for individual images.

Acknowledgements

Huge thanks to all the participants in the Generative Dog Images research competition for providing all the well-tuned models as well as feedback during the competition. The competition result analysis is published as a conference paper and if you find this dataset useful, please cite the following: @inproceedings{bai2021genmem, author = {Ching-Yuan Bai and Hsuan-Tien Lin and Colin Raffel and Wendy Chih-wen Kan}, title = {On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition}, booktitle = {Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)}, year = 2021, month = aug }

Inspiration

The Memorizaion-informed Fréchet Inception Distance (MiFID) was proposed and adopted as the benchmark metric during the competition to handle the training sample memorization issue. It works well in a competition setting but obvious flaws make it unideal in a general research setting.

Are there any other alternatives?

The large amount and great diversity of models in this dataset can serve as a testing ground for newly developed benchmark metrics.

IntroductionCanine atopic dermatitis (CAD) is a common inflammatory skin condition in dogs. It is a lifelong issue that poses a significant welfare concern due to the chronic skin discomfort and pruritus (itching) experienced by affected animals. Excessive scratching, licking, and chewing cause self-inflicted injuries to the skin and increase the risk of secondary infections. Several dog breeds, including Labrador Retriever, Boxer, and French Bulldog, are known to be predisposed to these issues, suggesting a genetic link to the condition.MethodsAccess to a large population of dogs genotyped on a medium-density single-nucleotide polymorphism (SNP) array through commercial Wisdom Panel testing, along with their linked clinical records, allowed a large-scale, highly powered genome-wide association study (GWAS) to be performed. In this study, over 28,000 dogs were examined to identify genetic changes associated with CAD.ResultsA statistically significant signal on canine chromosome 38 was identified, with a particularly strong signal in French Bulldogs. Whole-genome resequencing revealed a compelling splice donor variant in the signaling lymphocytic activation molecule 1 (SLAMF1), a transmembrane receptor with important functions in immune cells. Further analysis of additional genome sequences and RNA samples from the MARS PETCARE BIOBANK confirmed that the SLAMF1 splice variant is a strong potential contributor to an increased risk of atopic dermatitis.DiscussionThe discovery represents the first compelling genetic variant associated with CAD to be validated in more than one breed of dog. The study identifies SLAMF1 as a potential pharmaceutical target and the associated variant as a biomarker to enable dog breeders to make informed breeding decisions to reduce risk of CAD in future generations. The presence of the SLAMF1 variant in many dog breeds and free-roaming dogs worldwide, indicates its potential role in contributing to the global risk of CAD.

Over fifty participants, who together possessed broad research, veterinary and front-line expertise from across the canine health and welfare sector, contributed to a modified Delphi study to identify the highest priority research topics in UK canine health and welfare, the highest priorities for future research approaches, and the highest priorities for future reform in research processes and infrastructure, through group consensus. Further analysis also compared the prioritisation of selected research topics to the actual levels of research funding they previously received, through comparison with historical data. Most of the identified highest priority issues relating to canine health and welfare and its research concerned various aspects of the human-canine relationship, such as ownership or behavioural issues. Participants strongly emphasised the complexity of interrelated factors that impact the welfare of both dogs and people. Research topics identified as previously ‘most underfunded’ all concerned real-world canine welfare issues, particularly emphasising the breeding and supply of dogs. A supplementary analysis of historical research funding (2012–2022) for common chronic disorders in primary care practice, another identified highest priority topic, identified periodontal disease, anal sac disorders, overgrown nails and patellar luxation as the ‘most underfunded’ conditions. Most of the identified highest priority research approaches and methodologies concerned real-world design and execution aspects of canine health and welfare research, such as impact and engagement, with a strong focus on research investigating the human factors in canine welfare. Aspects of research funding infrastructure that were considered highest priority for future change mostly concerned increased transparency of funding processes and increased collaboration between stakeholder groups throughout the funding sector, which was strongly supported. Overall, these findings emphasise the importance of considering and including human factors and real-world impact, where appropriate, as key elements for optimising the relevance of canine health and welfare research.

BackgroundRabies is a notoriously underreported and neglected disease of low-income countries. This study aims to estimate the public health and economic burden of rabies circulating in domestic dog populations, globally and on a country-by-country basis, allowing an objective assessment of how much this preventable disease costs endemic countries.Methodology/Principal FindingsWe established relationships between rabies mortality and rabies prevention and control measures, which we incorporated into a model framework. We used data derived from extensive literature searches and questionnaires on disease incidence, control interventions and preventative measures within this framework to estimate the disease burden. The burden of rabies impacts on public health sector budgets, local communities and livestock economies, with the highest risk of rabies in the poorest regions of the world. This study estimates that globally canine rabies causes approximately 59,000 (95% Confidence Intervals: 25-159,000) human deaths, over 3.7 million (95% CIs: 1.6-10.4 million) disability-adjusted life years (DALYs) and 8.6 billion USD (95% CIs: 2.9-21.5 billion) economic losses annually. The largest component of the economic burden is due to premature death (55%), followed by direct costs of post-exposure prophylaxis (PEP, 20%) and lost income whilst seeking PEP (15.5%), with only limited costs to the veterinary sector due to dog vaccination (1.5%), and additional costs to communities from livestock losses (6%).Conclusions/SignificanceThis study demonstrates that investment in dog vaccination, the single most effective way of reducing the disease burden, has been inadequate and that the availability and affordability of PEP needs improving. Collaborative investments by medical and veterinary sectors could dramatically reduce the current large, and unnecessary, burden of rabies on affected communities. Improved surveillance is needed to reduce uncertainty in burden estimates and to monitor the impacts of control efforts.

This data set contains the free-running opportunities for tested dogs only on paths, paths and lawns in public green and recreational areas in accordance with Section 9 Paragraph 3 of the Hamburg Dogs Act in the Hanseatic City of Hamburg. Dogs that have successfully passed the obedience test and are therefore exempt from the general obligation to be on a leash are allowed to run free. After the exemption, the dogs may be carried unleashed wherever there are no "special" leash obligations and no bans on taking them with you. In addition to roads, paths and traffic areas - which are automatically approved for these dogs - there are also certain paths, paths and lawns in public green and recreational areas. The district offices have designated these areas so that they can be used as an additional service by dog ​​owners.

Hundreds of genetic variants associated with canine traits and disorders have been identified, with commercial tests offered. However, the geographic distributions and changes in allele and genotype frequencies over prolonged, continuous periods of time are lacking. This study utilized a large set of genotypes from dogs tested for the progressive rod-cone degeneration–progressive retinal atrophy (prcd-PRA) G>A missense PRCD variant (n = 86,667) and the collie eye anomaly (CEA)-associated NHEJ1 deletion (n = 33,834) provided by the commercial genetic testing company (Optigen/Wisdom Panel, Mars Petcare Science & Diagnostics). These data were analyzed using the chi-square goodness-of-fit test, time-trend graphical analysis, and regression modeling in order to evaluate how test results changed over time. The results span fifteen years, representing 82 countries and 67 breeds/breed mixes. Both diseases exhibited significant differences in genotype frequencies (p = 2.7 × 10−152 for prcd-PRA and 0.023 for CEA) with opposing graphical trends. Regression modeling showed time progression to significantly affect the odds of a dog being homozygous or heterozygous for either disease, as do variables including breed and breed popularity. This study shows that genetic testing informed breeding decisions to produce fewer affected dogs. However, the presence of dogs homozygous for the disease variant, especially for prcd-PRA, was still observed fourteen years after test availability, potentially due to crosses of unknown carriers. This suggests that genetic testing of dog populations should continue.

In the middle of the sixties Testologen AB, in cooperation with a group of advertisers, introduced a new way of investigation where data about the target groups, i.e. interests, consumer habits, possessions, buying intentions, and data about reading habits were collected in the same survey. At SSD there are now surveys available from the Sweden Now series covering the period 1972-1991. In the 1977 survey the respondents had to indicate their reading habits concerning fifteen different daily papers, weekdays and weekends respectively. They also had to state their reading habits concerning nearly fifty papers from the weekly and monthly press. Other questions dealt with the household´s possession of a number of capital goods such as, car, camera, projector, washing machine, dishwasher, etc., and also if there were any dogs, cats, aquarium fishes or cagebirds in the household. A group of questions is dealing with buying habits and purchasing intentions for a number of products. A number of questions about personal interests are introduced by ´Human interests are different. How great is your interest for the following subjects and activities´. Subsequently the respondent is asked how interested he/she is in buying food, cooking, having guests, leisure time activities, etc. Furthermore the respondents had to indicate if they agreed or disagreed with a number of statements concerning life style. There is information about the respondent´s gender, marital status, age, income, occupation, education and housing, and also about the household´s size, age structure, and total income of household. A major part of Sweden Now 1979 is a replication of earlier surveys. A new addition for this survey is a group of questions dealing with the respondents influence on purchases at the place of work. Purpose: Collect broad information about interests, purchasing habits and media choices Subset of Sweden Now 1979-II, covering the period 1979-03-26 to 1979-06-08. In the middle of the sixties Testologen AB, in cooperation with a group of advertisers, introduced a new way of investigation where data about the target groups, i.e. interests, consumer habits, possessions, buying intentions, and data about reading habits were collected in the same survey. At SSD there are now surveys available from the Sweden Now series covering the period 1972-1991. In the 1977 survey the respondents had to indicate their reading habits concerning fifteen different daily papers, weekdays and weekends respectively. They also had to state their reading habits concerning nearly fifty papers from the weekly and monthly press. Other questions dealt with the household´s possession of a number of capital goods such as, car, camera, projector, washing machine, dishwasher, etc., and also if there were any dogs, cats, aquarium fishes or cagebirds in the household. A group of questions is dealing with buying habits and purchasing intentions for a number of products. A number of questions about personal interests are introduced by ´Human interests are different. How great is your interest for the following subjects and activities´. Subsequently the respondent is asked how interested he/she is in buying food, cooking, having guests, leisure time activities, etc. Furthermore the respondents had to indicate if they agreed or disagreed with a number of statements concerning life style. There is information about the respondent´s gender, marital status, age, income, occupation, education and housing, and also about the household´s size, age structure, and total income of household. A major part of Sweden Now 1979 is a replication of earlier surveys. A new addition for this survey is a group of questions dealing with the respondents influence on purchases at the place of work. Syfte: Samla in en bred information om intressen, köpvanor och mediaval Delmängd av ORVESTO 1979-II omfattande perioden 1979-03-26 till 1979-06-08. Random sample selected from the Statistic Sweden population register over the total population (RTB). Probability: Simple random Sannolikhetsurval: obundet slumpmässigt urval Probability Sannolikhetsurval Self-administered questionnaire: paper Självadministrerat frågeformulär: papper COMMUNICATION AND L... Consumption and con... ECONOMICS EKONOMI KOMMUNIKATION OCH S... Konsumtion och kons... MEDIA Media Media Studies Media and Communica... Medie och kommunika... Medievetenskap Public relations Samhällsvetenskap Social Sciences attitudes attityder cognitive processes communications consumer goods consumption derived quantities domestic appliances egenskaper electrical equipment elektrisk utrustning equipment frekvens frequency fysiska egenskaper försäljningsställen hushållsapparat härledda storheter interest cognitive ... intresse kognitiva ... kognitiva processer kommunikation konsumtion konsumtionsvaror köp läsekrets mass communication mass media mass media use masskommunikation massmedia mediaanvändning naturvetenskaplig f... newspaper readership periodicals readership physical properties products produkter properties purchasing quantities readership retail outlets science and technology scientific research shopping storheter technology and inno... teknologi tidnings läsekrets tidskrifts läsekrets utrustning vetenskap och tekno...