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Abstract “Lifestyle politics” suggests that political and ideological opinions are strongly connected to our consumption choices, music and food taste, cultural preferences, and other aspects of our daily lives. With the growing political polarization this idea has become all the more relevant to a wide range of social scientists. Empirical research in this domain, however, is confronted with an impractical challenge; this type of detailed information on people’s lifestyle is very difficult to operationalize, and extremely time consuming and costly to query in a survey. A potential valuable alternative data source to capture these values and lifestyle choices is social media data. In this study, we explore the value of Facebook “like” data to complement traditional survey data to study lifestyle politics. We collect a unique dataset of Facebook likes and survey data of more than 6500 participants in Belgium, a fragmented multi-party system. Based on both types of data, we infer the political and ideological preference of our respondents. The results indicate that non-political Facebook likes are indicative of political preference and are useful to describe voters in terms of common interests, cultural preferences, and lifestyle features. This shows that social media data can be a valuable complement to traditional survey data to study lifestyle politics.

Increasing levels of political animosity in the United States invite speculation about whether polarization extends to aspects of daily life. However, empirical study about the relationship between political ideologies and lifestyle choices is limited by a lack of comprehensive data. In this research, we combine survey and Facebook Page "likes" data from more than 1,200 respondents to investigate the extent of polarization in lifestyle domains. Our results indicate that polarization is present in page categories that are somewhat related to politics – such as opinion leaders, partisan news sources, and topics related to identity and religion – but, perhaps surprisingly, it is mostly not evident in other domains, including sports, food, and music. On the individual level, we find that people who are higher in political news interest and have stronger ideological predispositions have a greater tendency to "like" ideologically homogeneous pages across categories. Our evidence, drawn from rare digital trace data covering more than 5,000 pages, adds nuance to the narrative of widespread polarization across lifestyle sectors and it suggests domains in which cross-cutting preferences are still observed in American life. [ABSTRACT FROM AUTHOR]

In this study we investigate whether social reference systems, such as Facebook “likes” (FBLs), promote sales in social commerce, wherein adverse selection and quality uncertainty often severely damage consumer trust and impede efforts to achieve sustainable growth. We also examine the extent to which product characteristics (product uncertainty and product franchising) and deal characteristics (tipping points, discount rates, and deal durations) moderate the social selling stimulated by FBLs. On the basis of 1,327 samples collected from a major social commerce platform provider, we identify several interesting empirical regularities regarding the relationship between FBLs and social commerce sales. The findings suggest that FBLs drive traffic and increase sales. Information technology artifacts and social technologies, such as FBLs, can endow a consumer’s shopping experience with a socialization component and induce social selling in collective buying platforms. Nevertheless, significant variations occur across products and deals. For example, consumers who purchase experience goods more frequently depend on FBLs than do those who buy search goods. FBLs exert a far greater influence on the sales of goods from independent stores than those from franchise chains. Social commerce consumers are unaffected by heavy discount rates as they make purchase decisions, but they extensively rely on FBLs, particularly when purchasing products that have low tipping points. Our results suggest that social commerce can be a powerful marketplace when the economic utility that is driven by price incentives is further strengthened and protected by the social utility that originates from trust and sharing. [ABSTRACT FROM PUBLISHER]

"Lifestyle politics" suggests that political and ideological opinions are strongly connected to our consumption choices, music and food taste, cultural preferences, and other aspects of our daily lives. With the growing political polarization this idea has become all the more relevant to a wide range of social scientists. Empirical research in this domain, however, is confronted with an impractical challenge; this type of detailed information on people's lifestyle is very difficult to operationalize, and extremely time consuming and costly to query in a survey. A potential valuable alternative data source to capture these values and lifestyle choices is social media data. In this study, we explore the value of Facebook "like" data to complement traditional survey data to study lifestyle politics. We collect a unique dataset of Facebook likes and survey data of more than 6500 participants in Belgium, a fragmented multi-party system. Based on both types of data, we infer the political and ideological preference of our respondents. The results indicate that non-political Facebook likes are indicative of political preference and are useful to describe voters in terms of common interests, cultural preferences, and lifestyle features. This shows that social media data can be a valuable complement to traditional survey data to study lifestyle politics. [ABSTRACT FROM AUTHOR]

Context: Despite being a nuclear power, Pakistan does not have satisfactory human development indicators. The 2018 United Nations Development Programme (UNDP) Human Development Index (HDI) ranking places it at 150 out of 189 countries, the lowest in the region after Afghanistan. Purpose: This article examines advocacy journalism coverage of human development issues versus other issues in the contents of mainstream Pakistani newspapers and investigates the factors behind the inadequate space give n to them. The study further explores the association between editorial and readers' priorities. Methods: The quantitative content analysis method is used to measure and compare the frequency of sample content in five categories coupled with qualitative in‐depth interviews with veteran journalists/academics to explain the factors that influence the editorial content. Findings: Rather than use precious space to comment on social hardship and ultimately improve the country's HDI value, editorial content is dominated by the discourse produced by the communication bureaucracies of powerful national and international establishments. Issues‐based policies of the state and political actors that do not concern human development, and warmongering and actual conflicts with India and Afghanistan, are given considerably greater coverage. Moreover, readers' reactions to editorial content through Facebook Likes indicate a clear difference between editorial and readers' priorities. Policy Implications: The communication aspects of development programmes should actively feed editorial boards regarding current global development agendas to ensure sufficient coverage of their advocacy. It is imperative to make the UNESCO‐led syllabus Teaching Journalism for Sustainable Development an integral part of the country's journalism curriculum. Relevant bodies should organize professional editorial training to raise awareness of how to use precious space wisely for the advocacy of development issues and how to be alert to the readers' priority issues. [ABSTRACT FROM AUTHOR]

Using data for the period 2010M06-2017M02, this study investigates the possibility of predicting total tourist arrivals to four Austrian cities (Graz, Innsbruck, Salzburg, and Vienna) from LIKES of posts on the Facebook pages of the destination management organizations of these cities. Google Trends data are also incorporated in investigating whether forecast models with LIKES and/or with Google Trends deliver more accurate forecasts. To capture the dynamics in the data, the autoregressive distributed lag (ADL) model class is employed. Taking into account the daily frequency of the original LIKES data, the mixed data sampling (MIDAS) model class is employed as well. While time-series benchmarks from the naive, error-trend-seasonal, and autoregressive moving average model classes perform best for Graz and Innsbruck across forecast horizons and forecast accuracy measures, ADL models incorporating only LIKES or both LIKES and Google Trends generally outperform their competitors for Salzburg. For Vienna, the MIDAS model including both LIKES and Google Trends produces the smallest forecast accuracy measure values for most forecast horizons. [ABSTRACT FROM AUTHOR]

The adoption of social media in political marketing has grown dramatically over the past ten years, as it creates two-way communication that stimulates and fosters candidates5 relationships with voters. However, can the count of "supporters" and "likes" recorded on the Facebook page of a candidate predict whether he/she will win the elections or not? In view of this, predicting an electoral outcome using "big" social media data is a new research topic that has emerged due to the exponential growth of social media. This study examines the extent to which political candidates5 use of Facebook fan pages and interaction with their supporters are related to the election outcomes (vote share and election success) of Taiwan's 2016 legislator election campaign. Facebook data were acquired for all 354 candidates. The findings indicate: a candidate's Facebook presence is related to his/her election outcomes. Positive correlations were also observed to exist between the numbers of supporters/likes candidates secured on their official fan pages and their popular vote share. Moreover, the "net-fans ratio" preliminary model, based on a candidate's likes/supporters and excluding those repeated with respective opponents, has an explanatory power to forecast regional legislators5 election outcome with 81.5% accuracy of all the seats, and with 87.9% accuracy of the seats of 6 major municipalities. Hence, Facebook data could be a significant indicator of electoral success. [ABSTRACT FROM AUTHOR]

Recently numerous studies are conducted to estimate the human personality from the online social activities. This paper develops a comprehensive model for political attitude estimation leveraging the Facebook Like information of the users. We designed a Facebook Crawler that efficiently collects data overcoming the difficulties in crawling Ajax enabled Facebook pages. We show that the category level selection can reduce the data analysis complexity utilizing the sparsity of the huge like-attitude matrix. In the Korean Facebook users’ context, only 28 criteria (3% of the total) can estimate the political polarity of the user with high accuracy (AUC of 0.82). [ABSTRACT FROM AUTHOR]

On social media, users can express their favorable attitudes toward messages that others post by clicking the “like” button. In return, they may also receive “likes” from others for their own posts. This study aims to examine the “liking” behavior on social media by using the theoretical framework of gift giving and impression management. Specifically, the study investigates if and how different personality traits (i.e., self-esteem, empathy, interpersonal generosity, and public self-consciousness) and demographic characteristics (i.e., gender, age, and education) are associated with one's frequencies of giving and receiving “likes” on Facebook. A survey was conducted with 421 Facebook users in the United States. The study results revealed that frequency of giving “likes” was positively associated with both interpersonal generosity and public self-consciousness, but frequency of receiving “likes” was not significantly related to the examined personality traits. Age and gender were significantly associated with frequencies of both giving and receiving “likes.” Educational background was negatively associated with giving “likes.” [ABSTRACT FROM AUTHOR]

Civic engagement on Facebook has evolved, but there are still few studies of people's motivations and reasons for liking humanitarian causes on Facebook. Introduced in 2009, the 'like' button has become a part of users' daily Facebook routines and a way for them to engage in humanitarian causes. Content analysis from a survey (N = 405) revealed six different liking practices for humanitarian causes on Facebook: 1) socially responsible liking; 2) emotional liking; 3) informational liking; 4) social performative liking; 6) low-cost liking; 7) routine liking. Interestingly, informational-driven liking was much less common than the more socially and emotionally motivated reasons for liking. The majority of the respondents also believe such likes help in promoting humanitarian causes; only a few had unliked such causes. The implications of these findings for understanding the nature and function of Facebook likes as a new form of civic engagement and humanitarian support are discussed. [ABSTRACT FROM AUTHOR]

• We explore links between receiving Facebook Likes, self-esteem and happiness. • We collect profile data consisting of Facebook updates and received Likes. • Updating frequency and upload of personal content lead to an increase in Likes. • Receiving Likes on Facebook is related to an increase in perceived happiness. • Self-esteem mediates the relationship between receiving Likes and happiness. For social media users, profile updating and receiving Likes may feel like a reward, and elicit positive emotions, reinforcing use of the platform. Could this mechanism have consequences for users' self-esteem and happiness? Previous findings on the topic are mixed, and typically limited by use of self-reports of online activity. In the present study, we used objective behavioral data to examine the hypotheses that receiving Likes on Facebook would relate to 1) users' level of perceived self-esteem, and 2) increased happiness via the mediating role of self-esteem. We recruited 2,349 adult Facebook users (589 men, 1,760 women; 67% aged 18–25, 26% aged 26–35, 7% aged > 35 years). Participants answered an online survey and provided access to their objective Facebook data (i.e., profile updates and received Likes). We found that frequency of users updating their profile and sharing personal content (e.g., self-generated texts, images, friends and location tags) had a direct effect on the frequency and intensity of the feedback (i.e., Likes) they received from other users in their online social network. Additionally, analyses supported a positive link between the frequency and intensity of positive feedback received by users and perceived happiness that was mediated in part by an increase in self-esteem. Overall, findings demonstrate a process linking positive online social feedback and perceived well-being. [ABSTRACT FROM AUTHOR]