An Empirical Study on Social Media Behaviour of Consumers and Social Media Marketing Practices of Marketers
Bibliographic record
Abstract
ABSTRACT The paper presents the results of a study on social media experience of consumers and marketers in the State of Punjab. The study is based upon two parallel surveys - one for marketers (N=101) and another for consumers (N=211), conducted during the first quarter of 2012. Self developed questionnaire (request to fill online questionnaire was sent through e-mail) has been used to elicit the perception about motives, beliefs, policies, specific actions, and experiences of marketers about Social Media Marketing (SMM). Another self developed on-line questionnaire containing indicators about consumer’s motives, beliefs, and experiences has been used to capture their perception about reasons for their presence on social media and factors (using Exploratory Factor Analysis) determining their social media behaviour. The respondents were requested to fill online questionnaires developed on Google Documents. Based on the results of the study and reviewed literature, the paper suggests the measures for effective Social Media Marketing (SMM) strategies. The findings of the study can be used by marketers and media planners for effective marketing results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".